Machine Learning

About Workshop

Introduction

One of the most Fascinating jobs of Century is Machine learning. Machine Learning is a subset of AI where the machine is trained to learn from its past experience. This Course is intended to guide developers new to machine learning through the beginning stages of their ML journey.

Course Outcome

On completion of the course students will be expected to: Have a good understanding of the fundamental issues and challenges of machine learning: data, model selection, model complexity, etc. Have an understanding of the strengths and weaknesses of many popular machine learning approaches.

Course Fees(6 weeks): 4000 INR 2400 INR

Course Start From: 15 May 2020




Day 1: Introduction to Machine Learning, its application in various domains
Day 2: Basics of Python (Conditional statements, Data structures)
Day 3: Introduction to Pandas
Day 4: Introduction to Numpy
Day 5: Visualization techniques (Matplotlib, Seaborn)

Day 1: Data Preprocessing techniques (Handling missing values, Encoding categorical variables, Feature Scaling, Train-Test Split).
Day 2: Introduction to Linear Regression (Simple and Multiple)
Day 3: Introduction to Linear Regression (Hands-on)
Day 4: Introduction to Logistic Regression (Theory)
Day 5: Introduction to Logistic Regression (Hands-on)
Minor Project 1

Day 1: Introduction to Decision Tree (Theory)
Day 2: Introduction to Decision Tree (Hands-on)
Day 3: Introduction to K-Nearest Neighbours (Theory)
Day 4: Introduction to K-Nearest Neighbours (Hands-on)
Day 5: Buffer day to cover left over topic, doubt clearing session

Day 1: Introduction to Support Vector Machine (Theory)
Day 2: Introduction to Support Vector Machine (Hands-on)
Day 3: Introduction to Naive Bayes (Theory)
Day 4: Introduction to Naive Bayes (Hands-on)
Day 5: Buffer day to cover left over topic, doubt clearing session
Day 7: One Day Hackathon based on algorithms learnt so far
Minor Project 2

Day 1: Introduction to K-Means Clustering (Theory)
Day 2: Introduction to K-Means Clustering (Hands-on)
Day 3: Hierarchical Clustering (Theory)
Day 4: Hierarchical Clustering (Hands-on)
Day 5: Buffer day to cover left over topic, doubt clearing session

Day 1: Introduction to Artificial Neural Networks (Theory)
Day 2: Introduction to Artificial Neural Networks (Hands-on)
Day 3: Introduction to Convolutional Neural Networks (Theory)
Day 4: Introduction to Convolutional Neural Networks (Hands-on)
Day 5: Buffer day to cover left over topic, doubt clearing session
Day 7: Final Hackathon Major Project 1


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