Generative Adversarial Networks

Facebook’s AI research director Yann LeCun called GAN “the most interesting idea in the last 10 years in ML. Generative Adversarial Networks are a powerful class of neural

A Comparative Study between R and Python for Text Data Processing

Data wants to change its form to useful information! Internet and interconnectivity of devices lead to the generation of data at a very high rate every

Software Quality Assurance and Machine Learning

Software Testing is a process of verifying and validating whether a software application is Bug-Free and built according to the requirements. Machine Learning, on the other

Scala for Big Data Engineering

Data Science as we all know is a combination of statistics and real-world programming. Data Scientists use a number of programming languages to extract insights and

Understanding Reinforcement Learning by solving Rubik’s Cube

By now, you must have become familiar with Reinforcement Learning along with buzz words such as environment, agent, policy, goal, and episode. We discussed this in

Statistical Techniques for every Data Science learner

This is an introductory article about the statistical aspects of data science. In this article, I will give a general overview of data science problems and

Facial Emotion Recognition for Classroom Video Analytics

Facial Emotion Recognition is the process of identifying human emotions from faces. It is one of the most applied concepts of computer vision and artificial intelligence.

Reinforcement Learning: Understand with a Simple Game

Reinforcement learning is an important type of Machine Learning where an agent learns how to behave in an environment by performing actions and seeing the results.

Making machine Understand Natural Language better with BERT

BERT stands for Bidirectional Encoder Representations from Transformer. It is a substantial addition to the league of various approaches dealing with finding a solution to understand

All you need to know about Attention

Attention Mechanism in deep learning has led to major performance improvements both in NLP and computer vision. All sequence models now implement attention resulting in state-of-the-art