Machine Learning with Python: From Linear Models to Deep Learning
- Machine learning methods are commonly used across engineering and sciences, from computer systems to physics. Moreover, commercial sites such as search engines, recommender systems (e.g., Netflix, Amazon), advertisers, and financial institutions employ machine learning algorithms for content recommendation, predicting customer behavior, compliance, or risk.
- As a discipline, machine learning tries to design and understand computer programs that learn from experience for the purpose of prediction or control.
- In this course, students will learn about principles and algorithms for turning training data into effective automated predictions.
- Computing for Data Analysis
- Introduction to Analytics Modeling
- Basic Programming Proficiency
- Probability Statistics
- Linear algebra
- Basic Calculus
What I will learn?
- Principles behind machine learning problems.
- learn classification, regression, clustering, and reinforcement learning
- Implement & Analyze linear models, kernel machines, neural networks & graphical models
- Implement and organize machine learning projects.
- Select suitable models for different applications.
- Self-paced learning
- Video tutorials
- Recognised certification
- Hours : 10-14 Hours Per Week
- Level :Advanced
- Price : Free