COURSE NAME
Machine Learning & Deep Learning Course
1. Machine Learning Course 
Python Basics
Conditionals, Loops and Functions
Lists and Dictionaries
2D Lists and Numpy
Pandas
Plotting Graphs
Introduction to ML
Linear Regression
MultiVariable Regression and Gradient Descent
Logistic Regression
Classification Measures
Decision Trees - 1
Decision Trees - 2
Feature Scaling
Random Forests
Naive Bayes
Project: Text Classification
KNN
SVM
PCA
PCA - 2
NLP - 1
NLP - 2
Git
Neural Networks - 1
Neural Networks - 2
Tensor Flow
Keras
CNN - 1
CNN - 2
RNN
LSTM
Unsupervised Learning - 1
Unsupervised Learning - 2
Git
Topics
Constants
Session
Variables
Placeholder
MNIST Data
Initialising Weights and Biases
Forward Propagation
Finding Predictions and Accuracy
Cost Function
Running the Optimizer
How does the Optimizer work ?
Running Multiple Iterations
