Introduction to Machine Learning | Machine Learning by Debabrata Bhakat [Episode 01/14]

Gradient Decent | Machine Learning Algorithm | Machine learning by Debabrata Bhakat [Episode 02/14]

Logistic Regression | Assumptions of Linear Regression | Machine learning by Debabrata Bhakat [Ep 2]

Method to improve machine learning model | Machine Learning by Debabrata Bhakat [Episode 04/14]

Coding implementation of a classification problems | Machine Learning by Debabrata Bhakat [EP 05/14]

Naive bayes classifier | Bayes theorem probability | Machine Learning by Debabrata Bhakat [EP 06/14]

Neural Networks | Machine Learning vs Deep Learning | Machine Learning by Debabrata Bhakat [EP 7/14]

Neural Network Gradient Descent | Activation Functions | Machine Learning by Debabrata Bhakat [EP 8]

K Means Clustering in Machine Learning | Machine Learning by Debabrata Bhakat [Episode 09/14]

Coding implementation of artificial neural network | Machine Learning by Debabrata Bhakat [EP 10/14]

[Private video]

Convolutional Neural Network (CNN) [Part 1] | Machine Learning by Debabrata Bhakat [Episode 11/14]

Convolutional Neural Network (CNN) [Part 2] | Machine Learning by Debabrata Bhakat [Episode 12/14]

Coding Implementation of CNN [Keras Classification] Machine Learning by Debabrata Bhakat [EP 13/14]

Introduction to RNN | Forward Propagation in RNN | Machine Learning by Debabrata Bhakat [EP 14/14]