Mathematics for Machine Learning
1. Introduction to Calculus
2. Introduction to Linear Algebra
3. Introduction to Probability & Statistics
Machine Learning Basics
1. Fundamentals of Machine Learning
2. Machine Learning Practical Applications: Classification, Regression etc.
3. Supervised Learning
4. Semi Supervised Learning
5.Unsupervised Learning
6. Neural Networks and Deep Learning
Practical Machine Learning
1. Machine Learning Frameworks : Python, Google COLAB, TensorFlow, Pytorch, Keras
2. Code Classification and Time series Prediction Models
3. Implementing a Neural Network from Scratch
Quiz
Apply CourseThis Machine Learning online course offers an in-depth overview of Machine Learning topics including working with real-time data, developing algorithms using supervised & unsupervised learning, regression, classification, and time series modeling. Learn how to use Python in this Machine Learning certification training to draw predictions from data.
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