Machine Learning Syllabus | Machine Learning Course Curriculum

Machine Learning

Course Description

This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning and deep learning algorithms like SVM, Artificial Neural Network, Convolutional Neural Network. This course is designed for beginners with some programming experience or experienced developers.

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Here is the Demo Video of this Course

Course Curriculum

Course Content

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Section 1: Introduction

Introduction to Machine Learning

Section 2: Python for data analysis

Section 3: Python for data visualization

Matplotlib (Part-1)

Matplotlib (Part-2)

Section 4: Linear Regression

Linear Regression (Part-1)

Linear Regression (Part-2)

Section 5: K Nearest Neighbors

Introduction to Supervised Learning

K Nearest Neighbors

Section 6: Comparing different classification models

Comparing classification models (Part-1)

Comparing classification models (Part-2)

Comparing classification models (Part-3)

Section 7: K means Clustering

K-means clustering

K-means clustering (Part-2)

Section 8: Unsupervised Learning

Apriori Algorithm (Part-1)

Apriori Algorithm (Part-2)

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