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Natural Language Processing – Sentiment Analysis using LSTM

This article aims to explain the concepts of NLP and how to build a model using LSTM a deep learning algorithm for performing sentiment analysis

Feature Engineering in Machine Learning

Learn the importance of feature engineering and how it can help you organize and optimize your data for better results in your projects. Read Now!

Key Python Packages for Data Science

In this article, learn about the basic python packages Pandas, NumPy, Scikit Learn, Matplotlib and Seaborn to help you analyze your data

Complete Guide to People Counting and Tracking: End-to-end Deep Learning Project

Deep learning is a byproduct of AI. Learn how to build an end-to-end deep learning project for people counting and tracking system

21 Reason why you should NOT become a Data Scientist

This article is a fun take on life as a data scientist. It describes the everyday situations a data scientist faces & how their life is different than others

How to Choose Evaluation Metrics for Classification Models

In this article, let us deep dive into the most common evaluation metrics for classification models that all data scientists should know

Recursive Feature Elimination (RFE): Working, Advantages & Examples

Recursive Feature Elimination: What id RFE, how does it work, examples, application, benefits, best practices, code, real world uses & more.

Genetic Algorithms and its use-cases in Machine Learning

The Game of Increasing R-squared in a Regression Model

R-squared is the degree to which the variance in the dependent variable can be explained by independent variable and is used in regression

A Measure of Bias and Variance – An Experiment

In this article we measure the bias and variance of a given model and observe the behavior of bias and variance w.r.t various ML models