Author Archives: Ajitesh Kumar

Ajitesh Kumar

I have been recently working in the area of Data Science and Machine Learning / Deep Learning. In addition, I am also passionate about various different technologies including programming languages such as Java/JEE, Javascript, Python, R, Julia etc and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc. I would love to connect with you on Linkedin and Twitter.

Different Activation Functions in Neural Networks

Data scientists know that activation functions are critical to understanding neural networks. It is important to use activation function in order to train the neural network. There are many activation functions available for data scientists to choose from, so it can be difficult choosing which activation function will work best for their needs. In this blog post, we look at different activation functions and provide examples of when they should be used in different types of neural networks. If you are starting on deep learning and wanted to know about different types of activation functions, you may want to bookmark this page for quicker access in future. Without further ado, …

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Posted in Deep Learning, Machine Learning. Tagged with , , .

Mean Squared Error vs Cross entropy loss function

In this post, you will be learning the difference between two common types of loss functions: Cross-Entropy Loss and Mean Squared Error (MSE) Loss. These are both used in machine learning for classification & regression tasks, respecitively, to measure how well a model performs on unseen dataset. Both these losses are ways of measuring how well the predictions are made by classification and regression algorithms, and they both provide different information about the performance of models. As a data scientist, it is very important for you to understand the difference between loss functions in a great manner. What is cross-entropy loss? Cross entropy loss is used in classification tasks where …

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Posted in Data Science, Machine Learning. Tagged with , .

Procurement: Key Advanced Analytics Use Cases

procurement analytics use cases

The procurement analytics applications are poised to grow exponentially in the next few years. With so much data available, it’s important to know how procurement analytics can help you make better business decisions. This blog will cover procurement analytics and key use cases of advanced analytics that will be useful for data scientists implementing different use cases using machine learning. It is aimed at procurement professionals and data scientists who would like to use procurement analytics for making better business decisions. With so much data available nowadays it’s important to know how procurement analytics can help you make the best decision possible based on cost, quality, Procurement analytics allows you …

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Posted in Data Science, Machine Learning, Procurement. Tagged with , , .

How do we build Deep Neural Network using Perceptron?

Single layer neural network

In this post, you will understand about how a deep neural network is built using a perceptron. This is a very important concept in relation to getting a good understanding of deep learning. You will also learn related Tensorflow / Keras code snippet. Here are the key concepts related to how deep neural network is built using one or more perceptrons: First and foremost, it is key to understand what is a Perceptron? A perceptron is the most fundamental unit which is used to build a neural network. A perceptron resembles a neuron in the human brain. In case of a neuron, multiple input signals are fed into a neuron …

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Posted in Data Science, Deep Learning, Machine Learning. Tagged with , .

Examples of Generative Adversarial Network (GAN)

In this post, you will learn examples of generative adversarial network (GAN). The idea is to put together some of the interesting examples from across the industry to get a perspective on what problems can be solved using GAN. As a data scientist or machine learning engineer, it would be imperative upon us to understand the GAN concepts in a great manner to apply the same to solve real-world problems. This is where GAN network examples will prove to be helpful. Here are some examples of GAN network usage. Text to image translation Image editing / manipulating Creating images (2-dimensional images) Recreating images of higher resolution Creating 3-dimensional object Text to …

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Posted in Data Science, Deep Learning, Machine Learning. Tagged with , , .

Perceptron Explained using Python Example

In this post, you will learn about the concepts of Perceptron with the help of Python example. It is very important for data scientists to understand the concepts related to Perceptron as a good understanding lays the foundation of learning advanced concepts of neural networks including deep neural networks (deep learning).  In this post, the following topics are covered: What is Perceptron? Perceptron Python code example What is Perceptron? Perceptron is a machine learning algorithm which mimics how a neuron in the brain works. It is also called as single layer neural network consisting of a single neuron. The output of this neural network is decided based on the outcome of just one activation …

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Posted in Data Science, Deep Learning, Machine Learning. Tagged with , , , .

50+ Machine learning & Deep learning Youtube Courses

In this post, you get an access to curated list of 50+ Youtube courses on machine learning, deep learning, NLP, optimization, computer vision, statistical learning etc. You may want to bookmark this page for quick reference and access to these courses. This page will be updated from time-to-time. Enjoy learning! Course title Course type URL MIT 6.S192: Deep Learning for Art, Aesthetics, and Creativity Deep learning https://www.youtube.com/playlist?list=PLCpMvp7ftsnIbNwRnQJbDNRqO6qiN3EyH AutoML – Automated Machine Learning AutoML https://ki-campus.org/courses/automl-luh2021 Probabilistic Machine Learning Machine learning https://www.youtube.com/playlist?list=PL05umP7R6ij1tHaOFY96m5uX3J21a6yNd Geometric Deep Learning Geometric deep learning https://www.youtube.com/playlist?list=PLn2-dEmQeTfQ8YVuHBOvAhUlnIPYxkeu3 CS224W: Machine Learning with Graphs Machine learning  https://www.youtube.com/playlist?list=PLoROMvodv4rPLKxIpqhjhPgdQy7imNkDn MIT 6.S897 Machine Learning for Healthcare Machine learning https://www.youtube.com/playlist?list=PLUl4u3cNGP60B0PQXVQyGNdCyCTDU1Q5j Deep Learning and Combinatorial Optimization Deep …

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Posted in Career Planning, Data Science, Deep Learning, Machine Learning, Tutorials. Tagged with , , , , .

Online AI News from Top Global Universities – List

US universities ai news and events

In this post, you will get an access to a list of web pages representing latest news related to artificial intelligence from top universities across the globe. This page will be updated from time-to-time for including new pages from different universities across the globe. These URLs will be very useful for those machine learning / data science enthusiasts who want to keep tab on current news and events in the field of artificial intelligence. MIT Stanford Stanford university – Human-centered AI (HAI) Stanford university – Center for AI in medicine and imaging Stanford AI research and ideas Harvard university JHU Malone center for Engg. in healthcare Yale university Princeton university …

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Posted in AI, Data Science. Tagged with , .

MOSAIKS for creating Climate Change Models

MOSAIKS models comparison with Resnet and pre-trained CNN models

In this post, you will learn about the framework, MOSAIKS (Multi-Task Observation using Satellite Imagery & Kitchen Sinks) which can be used to create machine learning linear regression models for climate change. Here is the list of few prediction use cases which has already been tested with MOSAIKS and found to have high model performance: Forest cover Elevation Population density Nighttime lights Income Road length Housing price Crop yields Poverty mapping What is MOSAIKS? MOSAIKS provides a set of features created from Satellite imagery dataset. We are talking about 90TB of data gathered per day from 700+ satellites. These features can be combined with machine learning algorithms to address global …

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Posted in AI, Climate Change, Data Science, Machine Learning. Tagged with , .

Machine Learning – Feature Selection vs Feature Extraction

Feature extraction vs feature selection

In this post, you will learn about the difference between feature extraction and feature selection concepts and techniques. Both feature selection and feature extraction are used for dimensionality reduction which is key to reducing model complexity and overfitting. The dimensionality reduction is one of the most important aspects of training machine learning models. As a data scientist, you must get a good understanding of dimensionality reduction techniques such as feature extraction and feature selection. In this post, the following topics will be covered: Feature selection concepts and techniques Feature extraction concepts and techniques When to use feature selection and feature extraction Feature Selection Concepts & Techniques Simply speaking, feature selection …

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Machine Learning for predicting Ice Shelves Vulnerability

ice shelves machine learning

In this post, you will learn about usage of machine learning for predicting ice shelves vulnerability. Before getting into the details, lets understand what is ice shelves vulnerability and how it is impacting global warming / climate change. What are ice shelves? Ice shelves are permanent floating sheets of ice that connect to a landmass. Most of the world’s ice shelves hug the coast of Antarctica. Ice from enormous ice sheets slowly oozes into the sea through glaciers and ice streams. If the ocean is cold enough, that newly arrived ice doesn’t melt right away. Instead it may float on the surface and grow larger as glacial ice behind it continues to flow into the …

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Posted in Climate Change, Data Science, Machine Learning. Tagged with , .

Python – Text Classification using Bag-of-words Model

Bag of words technique to convert to numerical feature vector

In this post, you will learn about the concepts of bag-of-words (BoW) model and how to train a text classification model using Python Sklearn. Some of the most common text classification problems includes sentiment analysis, spam filtering etc. In these problems, one can apply bag-of-words technique to train machine learning models for text classification. It will be good to understand the concepts of bag-or-words model while beginning on learning advanced NLP techniques for text classification in machine learning. The following topics will be covered in this post: What is a bag-of-words model? How to fit a bag-of-words model using Python Sklearn? How to fit a text classification model using bag-of-words technique? …

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Posted in Data Science, Machine Learning, Python. Tagged with , , .

Top Data Sources for Climate Change Research

climate change data sources

In this post, you will get to learn about top data sources online from where you can learn and get data for doing research on climate change. Vitalflux is committing itself to AI and climate change research for next 15 years. You will get to learn about climate change and how data science / machine learning can be leveraged to tackle climate change in time to come.   Without further ado, lets list down the data sources related to climate change research: United Kingdom’s Met Office Hadley Centre: Researchers at the Met Office Hadley Centre produce and maintain a range of gridded datasets of meteorological variables for use in climate monitoring and climate …

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Posted in Climate Change. Tagged with , .

Python Scraper for GoogleNews, Twitter, Reddit & Arxiv

Python scraper GoogleNews Twitter Reddit Arxiv

In this post, you will get the Python code for scraping latest and greatest news about any topics from Google News, Twitter, Reddit and Arxiv. This could prove to be very useful for data scientist, machine learning enthusiats to keep track of latest and greatest happening in the field of artificial intelligence. If you are doing some research work, these pieces of code would prove to be very handy to quickly access the information. The code in this post has been worked out in Google Colab notebook. First and foremost, import the necessary Python libraries such as the following for GoogleNews, Twitter and Arxiv.  Python Code for mining GoogleNews Here …

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Reddit Scraper Code using Python & Reddit API

Reddit app client id and secret token

In this post, you will get Python code sample using which you can search Reddit for specific subreddit posts including hot posts. Reddit API is used in the Python code. This code will be helpful if you quickly want to scrape Reddit for popular posts in the field of machine learning (subreddit –  r/machinelearning), data science (subreddit – r/datascience), deep learning (subreddit – r/deeplearning) etc.   There will be two steps to be followed to scrape Reddit for popular posts in any specific subreddits. Python code for authentication and authorization Python code for retrieving the popular posts Check the Reddit API documentation page to learn about Reddit APIs. Python code for …

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Mining Twitter Data – Python Code Example

Twitter data mining with Python Twitter API

In this post, you will learn about how to get started with mining Twitter data. This will be very helpful if you would like to build machine learning models based on NLP techniques.  The Python source code used in this post is worked out using Jupyter notebook. The following are key aspects of getting started with Python Twitter APIs.  Set up Twitter dev app and Python Twitter package Establish connection with Twitter Twitter API example – location-based trends, user timeline, etc Search twitter by hashtags Setup Twitter Dev App & Python Twitter Package In this section, you will learn about the following two key aspects before you get started with …

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Posted in Data Mining, Python. Tagged with , .