(Pre-requisites - ML - Level1

Upon successful completion, student will be promoted to project development

Lesson 1: Introduction to Machine Learning

Introduction to Data and Machine Learning

Lesson 2: Walking with Python

Understanding Python

Lesson 3: Machine Learning Techniques

Types of Learning

Supervised Learning

Unsupervised Learning

Advice for Applying Machine Learning

Machine Learning System Design

Lesson 4: Supervised Learning

Regression

Classification

Lesson 5: Supervised Learning - Regression

Predicting house prices: A case study in Regression

Linear Regression & Logistic: A Model-Based Approach

Regression fundamentals: Data and Models

Lesson 6: Supervised Learning - Classification

Analyzing the sentiment of reviews: A case study in Classification

Classification fundamentals : Data and Models

Understanding Decision Trees and Naive Bayes

Feature selection in Model building

Linear classifiers

Decision boundaries

Training and evaluating a classifier

False positives, false negatives, and confusion matrices

Classification ML block diagram

Lesson 7: Unsupervised Learning

Clustering

Recommendation

Deep Learning

Lesson 8: Unsupervised Learning - Clustering

Document retrieval: A case study in clustering and measuring similarity

Clustering System Overview

Clustering fundamentals : Data and Models

Feature selection in Model building

Prioritizing important words with tf-idf

Clustering and similarity ML block diagram

Lesson 9: Unsupervised Learning - Recommendation

Recommending Products

Recommender systems overview

Collaborative filtering

Understanding Collaborative Filtering and Support Vector Machine

Effect of popular items

Normalizing co-occurrence matrices and leveraging purchase histories

The matrix completion task

Recommendations from known user/item features

Recommender systems ML block diagram

Lesson 10: Unsupervised Learning – Deep Learning

Deep Learning: Searching for Images

Searching for images: A case study in deep learning

Learning very non-linear features with neural networks

Application of deep learning to computer vision

Deep learning performance

Demo of deep learning model on ImageNet data

Deep learning ML block diagram

#### Curriculum

## Machine Learning - L2

Empowering Kids with simple instructions

Course features:

1. Course instructions

2. Assignments every week