Revision Plan

Sl No	Revision Date	Topic	Link
Machine Learning Core
1	1	Regression	Maths Behind Linear, Multiple, Poly, Lasso and Ridge
2	2	Logistic Regression	Logistic Regression
3	3	K Nearest Neighbors	Maths Behind KNN
4	4,5	Decision Tree	Maths Behind Decision Tree
5	6,7	Support Vector Machine	Maths Behind SVM
6	8	Naive Bayes	Maths Behind Naive Bayes
7	9	K-Means Clustering	Maths Behind KMeans and DBScan
8	10,11,12	Principal Component Analysis	Maths Behind PCA
9	12,13	Ensemble learning, XGBoost and CatBoost	Maths Behind Ensemble learning
Machine Learning Extra
10	14	Precision and Scoring	Maths Behind Precision and Scoring
11	15	Correlation	Maths Behind Correlation
Deep Learning
1	1,2,3	Neural Networks Basics	Neural Networks Basics
2	4,5	Convolutional Neural Networks (CNNs)	Convolutional Neural Networks (CNNs)
3	6,7,8	Generative Adversarial Networks (GANs)	Generative Adversarial Networks (GANs)
4	9,10,11,12	Recurrent Neural Networks (RNNs)	Recurrent Neural Networks (RNNs)
5	13,14,15	Long Short-Term Memory (LSTM) Networks	Long Short-Term Memory (LSTM) Networks
6	16,17	Deep Reinforcement Learning	Deep Reinforcement Learning
7	18,19	Gated Recurrent Units (GRUs)	Gated Recurrent Units (GRUs)
8	20,21	Transfer Learning	Transfer Learning
9	22,23	Autoencoders	Autoencoders
10	24,25	Deep Learning Frameworks	Deep Learning Frameworks
11	26	LSTM and Time Series	LSTM