Course- Introduction to Machine Learning

OVERVIEW
CURRICULUM

Course Description

This Machine Learning course introduces students to the fundamentals of ML, starting from basic concepts to advanced techniques. Students will learn data preprocessing, model building, supervised and unsupervised algorithms, and deep learning. The course includes hands-on projects like predictive analytics, image classification, and NLP applications. By the end, students will gain practical skills to develop and deploy real-world ML models.

What you'll learn

Understand core concepts of Machine Learning and its types.
Perform data preprocessing, cleaning, and feature engineering.
Build and evaluate supervised and unsupervised ML models.
Utilize libraries like NumPy, Pandas, Matplotlib, and Scikit-Learn.
Develop deep learning models using TensorFlow and Keras.
Deploy ML models using Flask and cloud platforms.
Work on real-world projects like prediction, classification, and NLP.
Gain problem-solving and critical thinking skills for ML applications.

Requirements

Basic understanding of mathematics (algebra, probability, and statistics).
Familiarity with programming fundamentals (preferably Python).
Basic knowledge of computer operations and file handling.
Curiosity to learn and solve real-world problems.
No prior experience in Machine Learning required.

Introduction to Machine Learning

ML-History of Machine Learning

ML-AI vs ML vs Deep Learning

ML-What is Machine Learning

ML-Applications of ML

ML-Advantages & Disadvantages

ML-Types of Machine Learning

ML-Supervised Advantages

ML-Unsupervised Advantages

ML-Reinforcement Advantages

ML-Data Cleaning

ML-Encoding Categorical Variables

ML-Feature Scaling,Normalization

ML-Supervised Learning Algorithm

ML-Linear Regression

ML-Linear Regression Examples

ML-Types of Fit Linear Regression

ML-Polynomial Regression

ML-Polynomial Regression Example

ML-Polynomial Reg. Degree 3

ML-Polyn. Degree 2 vs Degree 3

ML-Decision Tree Regression

ML-Random Forest Regression

About Instructor

Hello Everybody, My Name is Gurpal Singh, working as a Assistant Professor in Khalsa College Patiala.

Teaching Experience: 13 Years

Area of Interest: Web Development, Programming Languages, Blockchain

INTRODUCTION TO MACHINE LEARNING

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Duration 12 Weeks
Lessons22
Language English
Skill Beginner
FeeRs.999/-

INTRODUCTION TO MACHINE LEARNING

Course Description

What you'll learn

Requirements

Introduction to Machine Learning

About Instructor

INTRODUCTION TO MACHINE LEARNING

Address

Contact

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