About the Course:
This live training provides a hands-on introduction to machine learning using Python. Participants will explore fundamental algorithms, build predictive models, and gain practical experience through interactive coding exercises.
Course Objective:
- Understand key concepts and principles of machine learning.
- Gain proficiency in implementing machine learning algorithms using Python libraries.
- Learn how to preprocess data, build models, and evaluate their performance.
- Acquire practical skills for solving real-world problems using machine learning techniques.
Who is the Target Audience?
- Aspiring data scientists, software engineers, researchers, and anyone interested in exploring machine learning with Python.
Basic Knowledge:
- Basic programming skills in Python and familiarity with linear algebra and statistics concepts would be beneficial.
Curriculum
Total Duration: 4 Hours
Introduction to Machine Learning
Python Libraries for Machine Learning (NumPy, pandas, scikit-learn)
Data Preprocessing and Feature Engineering
Supervised Learning: Regression and Classification
Unsupervised Learning: Clustering and Dimensionality Reduction
Model Evaluation and Validation Techniques
Homework Exercises