Basic Machine Learning Course

Python Programming

Statistical Inference

Data Analytics with Pandas

1. Introduction to Machine Learning

2. Regression Algorithms

   1. Linear Regression

   2. K Nearest Neighbours

   3. Decision Tree

3. Classification

   1. Logistic Regression

   2. K Nearest Neighbours

   3. Decision Tree

4. Parameter Tuning

   1. Cross Validation

   2. Hyper Parameter Tuning

5. Deep Learning Basics

   1. Neural Networks

   2. Linear Regression with Keras

6. Basic Evaluation Metrics

1. RMSE

2. MSE

3. Precision

4. Recall

5. Confusion Matrix

7. Time Series Analysis

5. 1. DateTime Transformations

   2. ARIMA

   3. SARIMA

   4. ML for TimeSeries

8. Unsupervised Learning

6. K-Means

7. Hierarchical Clustering

8. PCA