Browse Lessons

STATISTICS- What are Random Variables and It's Types and its Importance?

STATISTICS- Variance and Standard Devation

STATISTICS- Mean, Median And Mode Explained Easily

Saturday Live Q&A

What is AdaBoost (BOOSTING TECHNIQUES)

Why Python is the Best Programming Language For Machine Learning?

How To Get Data Science Jobs For Freshers

Online Courses for Data Science Specialization

How To Learn Data Science by Self Study and For Free

Do We Require Master OR PHD to Become Data Scientist?

Answering Your Questions and Some More Updates

Tutorial 2- Deployment of ML models in Heroku using FLASK

Tutorial 1- Deployment of Models- Premises VS IAAS vs PAAS cloud Platforms

How To Apply Data Science In Your Domain?

Tutorial 43-Random Forest Classifier and Regressor

Important Tools and Libraries Used By Data Scientist

Tutorial 42 - Ensemble: What is Bagging (Bootstrap Aggregation)?

How To Learn Data Science Smartly?

Tutorial 22- Padding in Convolutional Neural Network

The Role of Maths in Data Science and How to Learn?

Tutorial 21- What is Convolution operation in CNN?

Tutorial 20- Convolution Neural Network vs Human Brain

How To Handle Missing Values in Categorical Features

Cosine Similarity and Cosine Distance

Euclidean Distance and Manhattan Distance

Why Do I Teach? Motivations

Data Engineer vs Data Analyst vs Data Scientist

What Do A Data Scientist Do?

Why Do We Need to Perform Feature Scaling?

Different Types of Feature Engineering Encoding Techniques

How to Crack Data Science Interviews- Motivations

What should be your Salary Expectation as a Data Scientist?

Step By Step Transition Towards Data Science

Tutorial 37: Entropy In Decision Tree Intuition

Feature Engineering-How to Perform One Hot Encoding for Multi Categorical Variables

Complete Life Cycle of a Data Science Project

My Path on Becoming a Data Scientist- Motivation

Train Test Split vs K Fold vs Stratified K fold Cross Validation

What is Cross Validation and its types?

Tutorial 19- Training Artificial Neural Network using Google Colab GPU

Tutorial 18- Hyper parameter Tuning To Decide Number of Hidden Layers in Neural Network

Tutorial 17- Create Artificial Neural Network using Weight Initialization Tricks

Tutorial 5- Content Based Recommendation System

Tutorial 4- Book Recommendation using Collaborative Filtering

Tutorial 16- AdaDelta and RMSprop optimizer

Tutorial 3- Book Recommendation System using Pearson Correlation

Tutorial 2- Creating Recommendation Systems using Nearest Neighbors

Tutorial 1- Weighted hybrid technique for Recommender system