When building APIs, the need to upload files is expected, which can be images, text documents, scripts, pdfs, among others. In the development of this functionality, some problems can be found, such as the number of files, valid file types, sizes of these files, and several others. And to save us from these problems we have the Multer library. Multer is a node.js middleware for handling multipart/form-data that is used to send files in forms.
The first step is to create a NodeJS project on your computer.
\nIn your terminal, type the following command:
\nyarn add express* You can also use NPM for installation
\nCreate a file named app.js inside the src/ folder. The next step is to start our Express server in our app.js
const express = require("express")\nconst app = express()\n\napp.listen(3000 || process.env.PORT, () => {\n console.log("Server on...")\n})With the project created, configured and with Express installed, we will add the multer to our project.
\nyarn add multerThe next step is to import the multer into our app.js file.
const multer = require("multer")We are almost there. Now create a folder called uploads where we will store the uploaded files.
Now we are at a very important stage which is the configuration of diskStorage. DiskStorage is a method made available by multer where we configure the destination of the file, the name of the file and we can also add validations regarding the type of the file. These settings are according to the needs of your project. Below I will leave an elementary example of the configuration.
const storage = multer.diskStorage({\n destination: (req, file, cb) => {\n cb(null, "uploads/")\n },\n filename: (req, file, cb) => {\n cb(null, Date.now() + "-" + file.originalname)\n },\n})In the configuration above, we mentioned the destination for the uploaded files and also change the name of the file .
\nconst uploadStorage = multer({ storage: storage })\n\n// Single file\napp.post("/upload/single", uploadStorage.single("file"), (req, res) => {\n console.log(req.file)\n return res.send("Single file")\n})\n\n//Multiple files\napp.post("/upload/multiple", uploadStorage.array("file", 10), (req, res) => {\n console.log(req.files)\n return res.send("Multiple files")\n})In the code snippet above, we created 2 POST routes for sending files. The first /upload/single route receives only a single file, note that the uploadStorage variable receives our diskStorage settings. As a middleware in the route, it calls the single method for uploading a single file. The /upload/multiple route receives several files, but with a maximum limit of 10 files, note that the uploadStorage variable now calls the ʻarray` method for uploading multiple files.
With all the settings done, our little API is already able to store the files sent.
\nconst express = require("express")\nconst multer = require("multer")\n\nconst app = express()\n\nconst storage = multer.diskStorage({\n destination: (req, file, cb) => {\n cb(null, "uploads/")\n },\n filename: (req, file, cb) => {\n cb(null, Date.now() + "-" + file.originalname)\n },\n})\n\nconst uploadStorage = multer({ storage: storage })\n\n// Single file\napp.post("/upload/single", uploadStorage.single("file"), (req, res) => {\n console.log(req.file)\n return res.send("Single file")\n})\n//Multiple files\napp.post("/upload/multiple", uploadStorage.array("file", 10), (req, res) => {\n console.log(req.files)\n return res.send("Multiple files")\n})\n\napp.listen(3000 || process.env.PORT, () => {\n console.log("Server on...")\n})Now it's up to you!
\n","frontmatter":{"date":"October 12, 2020","updated_date":null,"description":"Learn how to upload files in a NodeJS application using Multer, Multer is a middleware for handling multipart/form-data that is used to send files in forms.","title":"Upload files using NodeJS + Multer","tags":["NodeJs","Express","Multer"],"pinned":null,"coverImage":{"childImageSharp":{"fluid":{"aspectRatio":1.5037593984962405,"src":"/static/7abf157b1bfeb7c65d7e338a620ac875/58556/node-multer-upload.webp","srcSet":"/static/7abf157b1bfeb7c65d7e338a620ac875/61e93/node-multer-upload.webp 200w,\n/static/7abf157b1bfeb7c65d7e338a620ac875/1f5c5/node-multer-upload.webp 400w,\n/static/7abf157b1bfeb7c65d7e338a620ac875/58556/node-multer-upload.webp 800w,\n/static/7abf157b1bfeb7c65d7e338a620ac875/99238/node-multer-upload.webp 1200w","sizes":"(max-width: 800px) 100vw, 800px"}}},"author":{"id":"Gabriel Rabelo","github":"gabrielrab","avatar":null}}}},{"node":{"excerpt":"Introduction Learning Deep Features for Discriminative Localization: Machine learning and Deep learning are gaining traction in today’s…","fields":{"slug":"/engineering/class-activation-mapping/"},"html":"Machine learning and Deep learning are gaining traction in today’s world and are making significant and unimaginable progress in almost every industry. However, with the increase in complexity and accuracy of these algorithms, the interpretability of these is at stake- especially the deep learning models which take in more than a million parameters for complex, convoluted models. Class Activation Mapping (CAM) is one such technique which helps us in enhancing the interpretability of such complex models.
\nFor a particular class (or category), Class activation mapping basically indicates the discriminative region of the image, which influenced the deep learning model to make the decision. The architecture is very similar to a convolutional neural network. It comprises several convolution layers, with the layer just before the final output performing Global Average Pooling. The features that are obtained are fed into the fully connected neural network layer governed by the softmax activation function and thus, output us the required probabilities. The importance of the weights with respect to a category can be found out by projecting back the weights onto the last convolution layer’s feature map.
\nThe Global Average Pooling (GAP) is preferred over Global Max Pooling (GMP) because GAP helps us in identifying the full extent of the object as compared to the GMP layer, which identifies one discriminative part. In Global Average Pooling, an average is taken across all the activation maps which help us to find all the possible discriminative regions present in them. Contrary to this, the Global Max Pooling method just considers the most discriminative region. Hence, Global Average Pooling showed better results than Global Max Pooling.
\nLet be the activation map of unit
in the last convolutional layer at spatial location
.
The result of GAP is represented as:-
\nFor a class c, an input to the softmax will be:-
\nOutput of Softmax layer:-
\nThus, the final equation for an activation map of class c would be:-
\n
The localization ability of the CAM method was put to the test when they were trained on the ILSVRC 2014 benchmark dataset. The CAM technique was used on popular CNN models like AlexNet, VGGNet and GoogLeNet by tweaking their models and fitting a GAP layer (similar to the CAM architecture) towards the end. This modified model was giving astounding results with the GAP layer as compared to their traditional architecture in terms of discriminative localization.
\nAfter applying a CAM architecture to fine-grained recognition and pattern discovery (like discovering informative objects in the scenes, concept localization in weakly labelled images, weakly supervised text detector and interpreting visual question answering), we can infer that feature capturing and localization was far more accurate in the CAM based GAP layer architecture, as the complete extent of the features were captured.\nVisualizing Class-specific Units:-\nWhen we use the GAP layer and the ranked softmax weight, we can directly visualize the units, which are the most discriminative for a particular class. Thus, CNN actually learns a bag of words, where each word is a discriminative class-specific unit. A combination of these class-specific units helps to guide CNNs in classifying each image.
\nCAMs are a great technique to interpret the information from the CNN models. However, the disadvantage of CAMs is that they can be noisy, and there might be some loss of spatial information. Hence, the Grad-CAM architecture and the Score-CAM architecture were built upon the CAM architecture to improve the accuracy, feature capturing and retain precise spatial information.
\n","frontmatter":{"date":"October 10, 2020","updated_date":null,"description":"Learn about the importance of the explainability of deep learning models and Class Activation Map Technique","title":"Class Activation Mapping in Deep Learning","tags":["Explainable AI","Deep Learning","CNN","Machine Learning"],"pinned":null,"coverImage":{"childImageSharp":{"fluid":{"aspectRatio":1.5037593984962405,"src":"/static/f00bfab91c9b545daddfe5a17abc22c8/58556/Cover.webp","srcSet":"/static/f00bfab91c9b545daddfe5a17abc22c8/61e93/Cover.webp 200w,\n/static/f00bfab91c9b545daddfe5a17abc22c8/1f5c5/Cover.webp 400w,\n/static/f00bfab91c9b545daddfe5a17abc22c8/58556/Cover.webp 800w,\n/static/f00bfab91c9b545daddfe5a17abc22c8/99238/Cover.webp 1200w","sizes":"(max-width: 800px) 100vw, 800px"}}},"author":{"id":"Ankit Choraria","github":"Ankit810","avatar":null}}}},{"node":{"excerpt":"What is data enrichment? and its importance Data enrichment is the process of combining first-party data from internal sources with…","fields":{"slug":"/engineering/full-data-science-pipeline-implementation/"},"html":"Data enrichment is the process of combining first-party data from internal sources with disparate data from other internal systems or third-party data from external sources.
\nUsually, the data available from clients or stakeholders are not enough to solve the given problem statement, like if a client comes with a problem statement to build a recommendation engine for his mutual fund industry, the usual data they have is old purchase data but that's not enough as client behaviour changes with time and is impacted by the present market condition, oil prices, etc. which needs to be incorporated in the model to make it efficient.
\nCodes for this tutorial is at Link
\nThe whole process id divided into four steps:
\nI have implemented a full pipeline of data science from scrapping data from web to implementing ml and NLP classification.
\nHere I have scraped data from IMDB website (imdb.py)
\nI have tried to implement simple ML regression on the data (ml_imdb.py)
\nI have prepared the data for NLP classification (multilabel_prep.py)
\nI have implemented multilabel NLP classifier using various techniques like chain classifier etc. (multilabelnlpclassifier.ipynb)
\nWeb scraping is the process of extracting and parsing raw data from the web. Web scraping is a technique which helps data scientist to make their data-rich and is an efficient technique of data collection.
\nThis world is full of data, but unfortunately, most of them are not in the form to be used. Data is like crude oil, or we say it is in unstructured form. For a data scientist or engineer, our first challenge is to make the data model consumption ready, which takes the majority of the time, and this whole process is collectively known as data preprocessing.
\nHTML is a form of primary markup language and the base framework of mostly all websites. For performing web scraping its necessary to know it
\nHere we will start with requesting the web page using python package requests.
\n from requests import get\n url = 'http://www.imdb.com/search/title?release_date=2017&sort=num_votes,desc&page=1'\n response = get(url)\n print(len(response.text))The whole web page is now stored in the variable object response.\nThen we parse the web page using beautifulsoup package.
\n from bs4 import BeautifulSoup\n html_soup = BeautifulSoup(response.text, 'html.parser')\n type(html_soup)Then I will store all the div with the class named lister-item mode-advanced in variable movie_containers.
\nmovie_containers = html_soup.find_all('div', class_ = 'lister-item mode-advanced')Then I iterate through this object and store the information in lists to make my final DataFrame, using simple for loops.
\n# Lists to store the scraped data in\nnames = []\nyears = []\nimdb_ratings = []\nmetascores = []\nvotes = []\n#gross=[] #many movies have no record\nmovie_description=[]\nmovie_duration=[]\nmovie_genre=[]\n# Extract data from individual movie container\nfor container in movie_containers:\n# If the movie has Metascore, then extract:\n if container.find('div', class_ = 'ratings-metascore') is not None:\n# The name\n name = container.h3.a.text\n names.append(name)\n# The year\n year = container.h3.find('span', class_ = 'lister-item-year').text\n years.append(year)\n# The IMDB rating\n imdb = float(container.strong.text)\n imdb_ratings.append(imdb)\n# The Metascore\n m_score = container.find('span', class_ = 'metascore').text\n metascores.append(int(m_score))\n# The number of votes\n vote = container.find('span', attrs = {'name':'nv'})['data-value']\n votes.append(int(vote))\n# Gross income of movie\n #gross_inc =container.find_all('span', attrs = {'name':'nv'})[1]['data-value']\n #gross.append(gross_inc)\n\n# movie description\n movie_desc=container.find_all('p', class_ = 'text-muted')[1].text\n movie_description.append(movie_desc)\n movie_det=container.find_all('p', class_ = 'text-muted')[0]\n\n\n# Movie duration\n movie_dur=movie_det.find('span',class_='runtime').text\n movie_duration.append(movie_dur)\n\n# Movie genre\n movie_gen=movie_det.find('span',class_='genre').text\n movie_genre.append(movie_gen)\n\nimport pandas as pd\none_df = pd.DataFrame({'movie': names,\n'year': years,\n'imdb': imdb_ratings,\n'metascore': metascores,\n'votes': votes,\n#'gross':gross,\n'movie decription':movie_description,\n'movie duration':movie_duration,\n'movie genre':movie_genre\n})\nprint(one_df.info())\none_df.to_csv('50_movie_details.csv')But this was only for one page which has data for 50 movies only which is not enough to build a model.
\nPlease refer my code to understand how I use simple for loops to iterate through all the movies and downloading data for 20 years(approx).
\nWhats is linear regression??
\nIt is one of the most popular and used statistical techniques\n• Used to understand the relationship between variables
\n• Can also be used to predict a value of interest for new observations
\n• The aim is to predict the value of a continuous numeric variable of interest (known as the response or dependent or target variable)
\n• The values of one or more predictor (or independent) variables are used to make the prediction
\n• One predictor = simple regression
\n• More predictors = multiple regression
\nHere I just tried to use metascore of movies firstly to predict IMDB ratings and secondly I wanted to enhance it by using metascore and votes to predict IMDB rating.
\n## ML model\n\nX = data.loc[:, 'metascore'].values\ny = data.loc[:, 'imdb'].values\n\n# Splitting the dataset into the Training set and Test set\nfrom sklearn.cross_validation import train_test_split\nX_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.33, random_state = 0)\n\nfrom sklearn.linear_model import LinearRegression\n\nregressor = LinearRegression()#making object for reg package\nregressor.fit(X_train.reshape(-1,1), y_train.reshape(-1,1))#to fit the regressor to our training data\n\n#predict the test results\ny_pred =regressor.predict(X_test.reshape(-1,1))\n\nfrom sklearn.metrics import mean_squared_error\nmean_squared_error(y_test, y_pred)\n\n# 0.18041462828221905## Let try with imdb and votes\nX1 = data.loc[:, ['metascore','votes']].values\ny1 = data.loc[:, 'imdb'].values\n\n# Splitting the dataset into the Training set and Test set\nfrom sklearn.cross_validation import train_test_split\nX_train, X_test, y_train, y_test = train_test_split(X1, y1, test_size = 0.33, random_state = 0)\n\nfrom sklearn.linear_model import LinearRegression\n\nregressor = LinearRegression()#making object for reg package\nregressor.fit(X_train, y_train)#to fit the regressor to our training data\n\n#predict the test results\ny_pred =regressor.predict(X_test)\n\n\nfrom sklearn.metrics import mean_squared_error\nmean_squared_error(y_test, y_pred)\n# 0.15729132122310804 good scoreI tried to scrape data from the IMDB site and then applied ML regression techniques on it. Later I found that the movies listed are multi-class like Logan belongs to Action, Drama, Sci-Fi, which led me to think about how to implement the classifier model in the multilabel data. Usually, the data we get in real-world is mostly multi labelled like chatbot data; the intent is many and like these movies which are multi-class.
\nHere we will first see how we prep our data for multilabel classification.
\nHere we have all tags in one single column which is not usable while we do classification, so we have to make separate columns for all labels, and if the row doesn't belong to that category, it will be filled by 0 else 1.
\nimport os\nos.chdir('Desktop/web_scraping/imdb scrapper_ml/')\n\nimport pandas as pd\n\ndata=pd.read_csv('multilabel_nlp_classification.csv')\n\nmovie_list=[x for x in data['movie genre']]\nmovie_list1=''\nfor x in data['movie genre']:\n movie_list1+=','+x\n\nli_m=movie_list1.split(',')\nli=[x.strip() for x in li_m]\nlist_s=list(set(li))\n\nfor x in list_s:\n data[x]=0\n\ndata['movie_genre']=[x.strip().split(',') for x in data['movie genre']]\n\nde=data.copy()\n#data.loc[0,'Action']=1\nde['id']=range(0,6116)\n#print(de.loc[de['id']==0,'Action'])\nfor i in range(0,6116):\n for x in de.loc[de['id']==i,'movie_genre']:\n for y in x:\n y=y.strip()\n de.loc[de['id']==i,y]=1\n\nde.to_csv('multilabel_nlp_classification.csv')Now, as our data is ready, we can start with NLP implementation.
\nFor multilabel classification, I used techniques like classifier chain, label powerset, etc.
\nHere the problem statement is that using the movie description our model has to guess which genre the movie belongs to. It is a popular use case. Take an example of ecommerce product description data; now instead of manually assigning the labels to it, we can use a model which will find relevant labels or genre for it and make the content relevant to the type it belongs.
\nI start with Exploratory data analysis and then data cleaning, which is the most crucial step as if all the description has some very 30-50 common words it will simply make the data-heavy and model slow and inefficient.
\nThen we go on to make the data model ready as ML models don't understand text data we have to feed numbers in it. For that purpose, we use TfidfVectorizer.
\nTfidfVectorizer - Transforms text to feature vectors that can be used as input to the estimator.
\nThen simply diving the data in train and test split.
\nx_train = vectorizer.transform(train_text)\ny_train = train.drop(labels = ['id','movie decription'], axis=1)\n\nx_test = vectorizer.transform(test_text)\ny_test = test.drop(labels = ['id','movie decription'], axis=1)I tried first with applying logistic regression and one vs rest classifier.
\nOneVsRestClassifier strategy splits a multi-class classification into one binary classification problem per class.\nOneVsRestClassifier is when we want to do multi-class or multilabel classification, and its strategy consists of fitting one classifier per class. For each classifier, the class is fitted against all the other classes.
\n# Using pipeline for applying logistic regression and one vs rest classifier\nLogReg_pipeline = Pipeline([\n ('clf', OneVsRestClassifier(LogisticRegression(solver='sag'), n_jobs=-1)),\n ])\n\nfor category in categories:\n printmd('**Processing {} comments...**'.format(category))\n \n # Training logistic regression model on train data\n LogReg_pipeline.fit(x_train, train[category])\n \n # calculating test accuracy\n prediction = LogReg_pipeline.predict(x_test)\n print('Test accuracy is {}'.format(accuracy_score(test[category], prediction)))\n print("\\n")Next, I tried with BinaryRelevance
\nIt is a simple technique which treats each label as a separate single class classification problem.
\n# using binary relevance\nfrom skmultilearn.problem_transform import BinaryRelevance\nfrom sklearn.naive_bayes import GaussianNB\n\n# initialize binary relevance multi-label classifier\n# with a gaussian naive bayes base classifier\nclassifier = BinaryRelevance(GaussianNB())\n\n# train\nclassifier.fit(x_train, y_train)\n\n# predict\npredictions = classifier.predict(x_test)Next, I tried using ClassifierChain.
\nIt is almost similar to BinaryRelevance, here the first classifier is trained just on the input data, and then each next classifier is trained on the input space and all the previous classifiers in the chain.
\nfrom skmultilearn.problem_transform import ClassifierChain\nfrom sklearn.linear_model import LogisticRegression\n\n\n# initialize classifier chains multi-label classifier\nclassifier = ClassifierChain(LogisticRegression())\n\n# Training logistic regression model on train data\nclassifier.fit(x_train, y_train)\n\n# predict\npredictions = classifier.predict(x_test)Next, I tried using Label Powerset.
\nHere we transform the problem into a multi-class problem with one multi-class classifier is trained on all unique label combinations found in the training data.
\nfrom skmultilearn.problem_transform import LabelPowerset\n# initialize label powerset multi-label classifier\nclassifier = LabelPowerset(LogisticRegression())\n\n# train\nclassifier.fit(x_train, y_train)\n\n# predict\npredictions = classifier.predict(x_test)Please refer my notebook multilabelnlpclassifier.ipynb from my repo for more details.
\nThe two types of email you can send and receive are plain text emails (any email that contains just plain old text with no formatting) and HTML emails, these are formatted and styled using HTML and inline CSS.\nHTML email is the use of HTML to provide formatting and semantic markup capabilities in an email that are not available in plain text.
\nAn HTML email is designed just like a website with the help of graphics, table columns, colors and links. A non-programmer can also create it since email marketing services provide flexible campaign builders. Email client vendors have not been as developing as web browser vendors in adopting new standards.
\nDefinition
\nEmails which are formatted using Hypertext Markup Language(HTML), as opposed to plain text email.
\nHow to Create an HTML Email
\nMany tools that create and send an email will offer pre-formatted, already built HTML templates that allow you to design emails without knowing or accessing any code of back-end.
\nThe best way to understand any process is to do it yourself, from level zero. We make any changes in the email editor; those changes will be automatically coded into the final result. This email building tool is the best option if you don't have an email designer, but you still want to send any professional marketing emails.
\nIf you want more control over the code of your emails and you are comfortable with HTML(that is just basic and easy), most email tools will allow you to import HTML files directly for using it as custom email templates. They have a wide variety of free HTML email templates available on the internet, and if you are familiar with HTML, it is a straightforward process to use that template in the email building tool of your own choice.
\nTo create an HTML email from scratch, you will need to have advanced knowledge of HTML. Because creating an HTML email from scratch can be quite tricky, we recommend you to work with a developer for this process, or you may go with a template for an easy process.
\nIf you choose to code your HTML email by hand, these are the necessary steps you need to use while creating HTML email:
\nHow to send HTML emails through Outlook?
\nYou can check HTML Email Template here:
\n\n","frontmatter":{"date":"October 09, 2020","updated_date":null,"description":"If you choose to code your HTML email by hand, there are many different things you need to use while creating HTML email.","title":"HTML Email Concept","tags":["Html","Email"],"pinned":null,"coverImage":{"childImageSharp":{"fluid":{"aspectRatio":1.7699115044247788,"src":"/static/67ac86643dbb14dedfd4fe52ff7e659c/58556/email_picture.webp","srcSet":"/static/67ac86643dbb14dedfd4fe52ff7e659c/61e93/email_picture.webp 200w,\n/static/67ac86643dbb14dedfd4fe52ff7e659c/1f5c5/email_picture.webp 400w,\n/static/67ac86643dbb14dedfd4fe52ff7e659c/58556/email_picture.webp 800w,\n/static/67ac86643dbb14dedfd4fe52ff7e659c/54d25/email_picture.webp 1080w","sizes":"(max-width: 800px) 100vw, 800px"}}},"author":{"id":"Nivedita Singh","github":"Nivedita967","avatar":null}}}},{"node":{"excerpt":"Identity-as-a-service or IDaaS refers to cloud-based identity and access management solutions that are offered on a subscription basis. At…","fields":{"slug":"/identity/best-idaas-provider-loginradius/"},"html":"Identity-as-a-service or IDaaS refers to cloud-based identity and access management solutions that are offered on a subscription basis. At its core, IDaaS delivers access, intelligence, and identity governance capabilities to consumers' systems.
\nInterestingly, IdaaS has been experiencing exponential growth in recent years. So, to understand this rapid surge in the best IDaaS providers, let's go back a little.
\nConsumers have already been exploring and utilizing the online facilities—from transactions, education, work, shopping, entertainment, to medicines—for some time now. They want frictionless, non-invasive, and seamless solutions.
\nSo, how are companies delivering instant, personalized gratification? The basis for most is identity.
\nConsumers want identity solutions to be easy and simple-to-use.
\nData privacy is another prerequisite necessity. In fact, a survey by Gemalto finds out that 71% of consumers choose to opt-out of a company that experienced a data breach. Talk about a dealbreaker!
\nLikewise, there are also key questions about data privacy, ownership, control, and scalability. Scoring these areas on a firm ground will make a good ID solution. A growing number of companies are already working on this goal.
\nThe best IDaaS providers are evolving, and new ones are emerging. How do you choose the right one?
\n![\"Best](\"/0dba2e23e64a52e959fe1feeb8344cc8/Best-IDaaS-solution-1.webp\")
1. It should connect to mixed platform environments.
\nA lot of organizations (especially enterprise-level) still prefer the hybrid approach to host their business applications, i.e. both on-premises and in the cloud. The best IDaaS providers will offer consumers seamless access from a variety of devices, or mostly when legacy solutions are involved.
\nIt should not matter where the applications are hosted or accessed, the IDaaS solution should simplify integration and create a simplified, smooth, and unified consumer experience.
\n2. It should deliver better security.
\nWith a modern cloud identity platform comes security with modern techniques. Identity theft and network compromise are a big problem that IT managers face today, and the lack of passwords is a major explanation for these breaches.
\nThere should be a large number of security techniques included as the identity management platform transitions to the cloud. Examples include one-way password hashing, salting that secures communication between all vulnerable end-points.
\n3. It should verify and manage all identities.
\nWith modern industries requiring robust access and security policies, the best IDaaS provider should include identity management tools for different use cases.
\nFor example, when new devices, applications, and consumers are introduced, or third-party relationships are integrated, the access requirement and priorities are also changed. Your IDaaS provider should be able to access authorized resources without having to authenticate and sign in separately to each application.
\nMoreover, your IDaaS solutions provider should also include frameworks for single sign-on (SSO) and federated identity with multi-factor authentication (MFA) that removes silos and enables uninterrupted network environments.
\n4. It should offer a complete app access lifecycle management.
\nWhen a new user joins your organization or an existing user takes on a different role, your IDaaS solution should make provisioning easier with automatic account creation, role-based authorization management, single sign-on, and automated account deprovisioning.
\nA comprehensive, automated app access lifecycle management eliminates helpdesk calls, reduces IT burden, and saves time. It is also easier to offboard users by instantly removing access and deactivating app accounts.
\n5. It should offer multi-factor authentication (MFA).
\nConsumers aren't confined to just the one network, device, or applications today. They have to remember a lot of passwords for different accounts. But then, passwords alone cannot be trusted to keep accounts secure. You need a stronger authentication factor at a granular level and MFA should do the trick.
\nThe best IDaaS provider should include MFA with (at least) the following combination:
\nAlso, ensure that your IDaaS provider offers custom configurations, whenever necessary for optimal performance. Make sure it is affordable, flexible, and designed to scale (forecasting your rapid growth).
\n![\"Guide-to-Modern-Customer-Identity-ebook\"](\"/cb344658920387aac010223f2c1d79a1/EB-Guide-to-Modern-Customer-Identity.webp\")
LoginRadius is credible and the best IDaaS provider that can be applied to any situation where consumers expect to connect securely to organizations' IT resources.
\nThe platform offers next-gen technology to make sure employees, consumers, clients, or partners are who they say they are. Once confirmed, it offers access rights to resources based on the roles and permissions granted.
\nAdditionally, the LoginRadius IDaaS is deployed through the cloud—meaning businesses can request access securely, irrespective of the location or device.
\nLet's find out the key capabilities that make LoginRadius an interesting pick for developers and businesses, in general.
\nIt is incredibly important for IT professionals to safeguard systems and data while providing easy, convenient access to consumers and clients. Only the best IDaaS provider can offer reliable security that businesses require.
\nLoginRadius is the comprehensive ideal solution for enterprises who need to implement identity management into applications quickly and easily.
\n![\"book-a-free-demo-loginradius\"](\"/788a6a84e389edac18728007099fdc1d/Book-a-free-demo-request.webp\")
These days we have all come across one of the coolest buzzwords in the IT industry: \"The Blockchain\". It might seem to be a new magic word in the market that companies spell interest in their businesses. However, the complexity of it is incredibly far-reaching. Blockchain integrates the openness and flexibility of the internet with the security of cryptography to come out with a safer, faster way of verification of information and most importantly establishes trust in this open world.
\nBlockchain was first developed by an anonymous programmer or group of programmers known by a name 'Santoshi Nakamoto'.It was an underlying technology for the Bitcoin, which is used for peer-to-peer transactions. Blockchain at its heart is a list of transactions like a distributed ledger open to all in the network. It stores the data in such a way that it seems virtually impossible to add, update or remove any information stored without the notice of other users in a peer-to-peer network.
\nBlockchain mainly performs two tasks: collect and order data in blocks- similar to the traditional computer database and then chain them securely using cryptography.
\nLet us take a closer look at each block in this enormous chain –
\n![\"Blockchain\"](\"/b84871cea75ab42c2a7a93163787f5e5/block.webp\")
The copy of the complete blockchain is with all the participants so that they can detect tampering if the hash matches across the chain then everyone knows that it is trustworthy.\nBlockchain is an emerging technology but has been evolving ever since its innovation. This technology has the unlimited potential to bring about an upheaval in the way everyone- organisations, governments, individuals work together. It promises a simple, secure, paperless path to establish trust for virtual transactions of money, products and other confidential information worldwide.
\nBlockchain is one of the technologies that has gained popularity from its very birth, and now it is being used in many fields.
\nIn financial markets, trade is very dynamic where there is the exchange of money, assets involving multiple banks; this may lead to unexpected errors. To reduce this bottleneck blockchain came up with the idea of smart contracts which is a small computer program that describes the transactions step by step combining multiple blockchains, multiple assets and executes the transactions securely.
\nBlockchain can keep track of many commercial transactions and efficiently hold sensitive information. A digital id via blockchain secures the data stored and can be used worldwide in your fingertips.
\nBlockchain can be very handy in monitoring the supply chain in food and manufacturing industries by removing paper-based trails and also removing intermediaries between producers to customers. Not just the above applications it is used in many more places and has changed, is going to change the world around us.
\nThough it is a new technology, it has an enormous ability to transform everything existing now. As a coin has its two faces, blockchain technology also has some glitches as it can destroy the middlemen in many of the industries.\nBlockchain has already spread its root firmly in soils of the new world, and the swarm of transformation has already begun. It is the responsibility of all the young generation to make complete usage of this technology as it matures and make it to become a huge money plant.
\n","frontmatter":{"date":"October 08, 2020","updated_date":null,"description":"Learn about Blockchain technology and how it works.","title":"Blockchain: The new technology of trust","tags":["Blockchain","Cyber Security"],"pinned":null,"coverImage":{"childImageSharp":{"fluid":{"aspectRatio":1.6666666666666667,"src":"/static/01f18fbf0dec445fa25aa3b13483883e/58556/CoverPage.webp","srcSet":"/static/01f18fbf0dec445fa25aa3b13483883e/61e93/CoverPage.webp 200w,\n/static/01f18fbf0dec445fa25aa3b13483883e/1f5c5/CoverPage.webp 400w,\n/static/01f18fbf0dec445fa25aa3b13483883e/58556/CoverPage.webp 800w,\n/static/01f18fbf0dec445fa25aa3b13483883e/1fb14/CoverPage.webp 960w","sizes":"(max-width: 800px) 100vw, 800px"}}},"author":{"id":"Shraddha V Prasad","github":"shraddhavp","avatar":null}}}}]},"markdownRemark":{"excerpt":"Identity is evolving, and developers are at the forefront of this transformation. Every day brings a new learning—adapting to new standards…","fields":{"slug":"/identity/developer-first-identity-provider-loginradius/"},"html":"Identity is evolving, and developers are at the forefront of this transformation. Every day brings a new learning—adapting to new standards and refining approaches to building secure, seamless experiences.
\nWe’re here to support developers on that journey. We know how important simplicity, efficiency, and well-structured documentation are when working with identity and access management solutions. That’s why we’ve redesigned the LoginRadius website—to be faster, more intuitive, and developer-first in every way.
\nThe goal? Having them spend less time searching and more time building.
\nLoginRadius’ vision is to give developers a product that simplifies identity management so they can focus on building, deploying, and scaling their applications. To enhance this experience, we’ve spent the last few months redesigning our interface— making navigation more intuitive and reassuring that essential resources are easily accessible.
\nHere’s a closer look at what’s new and why it’s important:
\n![\"This](\"/f46881583c7518a93bb24e94c32320de/a-developer-friendly-dark-theme.webp\")
Developers spend long hours working in dark-themed IDEs and terminals, so we’ve designed the LoginRadius experience to be developer-friendly and align with that preference.
\nThe new dark mode reduces eye strain, enhances readability, and provides a seamless transition between a coding environment and our platform. Our new design features a clean, modern aesthetic with a consistent color scheme and Barlow typography, ensuring better readability. High-quality graphics and icons are thoughtfully placed to enhance the content without adding visual clutter.
\nSo, whether you’re navigating our API docs or configuring authentication into your system, our improved interface will make those extended development hours more comfortable and efficient.
\n![\"This](\"/e5358b82be414940f3fb146013845933/capabilities.webp\")
We’ve restructured our website to provide a straightforward breakdown of our customer identity and access management platform capabilities, helping you quickly find what you need:
\nThis structured layout ensures you can quickly understand each capability and how it integrates into your identity ecosystem.
\n![\"This](\"/a8c155c2b6faf3d5f4b4de4e2b14d763/developers-menu.webp\")
We’ve been analyzing developer workflows to identify how you access key resources. That’s why we redesigned our navigation with one goal in mind: to reduce clicks and make essential resources readily available.
\nThe new LoginRadius structure puts APIs, SDKs, and integration guides right at the menu bar under the Developers dropdown so you can get started faster. Our Products, Solutions, and Customer Services are also clearly categorized, helping development teams quickly find the right tools and make informed decisions.
\n![\"This](\"/b2f9a964a2da0ea83e2f8596b833bba7/we-support-your-tech-stack.webp\")
Developers now have a clear view of the tech stack available with LoginRadius, designed to support diverse business needs.
\nOur platform offers pre-built SDKs for Node.js, Python, Java, and more, making CIAM integration seamless across popular programming languages and frameworks.
\nCheck out our revamped LoginRadius website and see how the improved experience makes it easier to build, scale, and secure your applications.
\nDo not forget to explore the improved navigation and API documentation, and get started with our free trial today. We’re excited to see what you’ll build with LoginRadius!
\n","frontmatter":{"date":"February 21, 2025","updated_date":null,"description":"LoginRadius’ vision is to give developers a product that simplifies identity management so they can focus on building, deploying, and scaling their applications. To enhance this experience, we’ve redesigned our website interface, making navigation more intuitive and reassuring that essential resources are easily accessible.","title":"Revamped & Ready: Introducing the New Developer-First LoginRadius Website","tags":["Developer tools","API","Identity Management","User Authentication"],"pinned":true,"coverImage":{"childImageSharp":{"fluid":{"aspectRatio":1.7857142857142858,"src":"/static/80b4e4fbe176a10a327d273504607f32/58556/hero-section.webp","srcSet":"/static/80b4e4fbe176a10a327d273504607f32/61e93/hero-section.webp 200w,\n/static/80b4e4fbe176a10a327d273504607f32/1f5c5/hero-section.webp 400w,\n/static/80b4e4fbe176a10a327d273504607f32/58556/hero-section.webp 800w,\n/static/80b4e4fbe176a10a327d273504607f32/99238/hero-section.webp 1200w,\n/static/80b4e4fbe176a10a327d273504607f32/7c22d/hero-section.webp 1600w,\n/static/80b4e4fbe176a10a327d273504607f32/1258b/hero-section.webp 2732w","sizes":"(max-width: 800px) 100vw, 800px"}}},"author":{"id":"Rakesh Soni","github":"oyesoni","avatar":"rakesh-soni.webp"}}}},"pageContext":{"limit":6,"skip":708,"currentPage":119,"type":"///","numPages":164,"pinned":"ee8a4479-3471-53b1-bf62-d0d8dc3faaeb"}},"staticQueryHashes":["1171199041","1384082988","2100481360","23180105","528864852"]}