Introduction to Machine Learning & Deep Learning in Python

Introduction to Machine Learning & Deep Learning in Python
Regression, Naive Bayes Classifier, Support Vector Machines, Random Forest Classifier and Deep Neural Networks

This course is about the fundamental concepts of machine learning, focusing on regression, SVM, decision trees and neural networks. These topics are getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detect cancer for example or we may construct algorithms that can have a very good guess about stock prices movement in the market.

In each section we will talk about the theoretical background for all of these algorithms then we are going to implement these problems together. We will use Python with Sklearn, Keras and TensorFlow.

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Who this course is for:
  • This course is meant for newbies who are not familiar with machine learning or students looking for a quick refresher


Deep Learning Prerequisites: Logistic Regression in Python

Ensemble Machine Learning in Python: Random Forest, AdaBoost

Machine Learning and AI: Support Vector Machines in Python

Learn Python Through Exercises

Machine Learning Intro for Python Developers

Hands-On Machine Learning: Learn TensorFlow, Python, & Java!