This training program is divided into 5 segments which will be covered over the course of 6 Days. Each segment will deal with both theoretical and practical knowledge so that the learners can implement their learnings to work.
1.) Statistical Learning
Statistical Analysis Concepts
Introduction to Probability
Bayes’ Theorem
Hypothesis Testing and Scores
2)Machine Learning with Python
Overview
Pandas - Data Analysis
Matplotlib - Statistical Analysis
Scikit Learn - Data Visualization
3)Introduction to Machine Learning
Machine Learning Modeling Flow
How to treat Data in ML
Bias-Variance Trade-Off
Overfitting and Underfitting
4)Optimisation
Maxima and Minima
Cost Function
Learning Rate
Optimization Techniques
5)Types Of Machine Learning
Supervised Learning
Unsupervised Learning
Reinforcement learning
