Introduction to Machine Learning & Deep Learning in Python

Regression, Naive Bayes Classifier, Support Vector Machines, Random Forest Classifier and Deep Neural Networks

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Introduction to Machine Learning & Deep Learning in Python
Introduction to Machine Learning & Deep Learning in Python

Introduction to Machine Learning & Deep Learning in Python udemy course free download

Regression, Naive Bayes Classifier, Support Vector Machines, Random Forest Classifier and Deep Neural Networks

What you'll learn:

  • Solving regression problems
  • Solving classification problems
  • Using neural networks
  • The most up to date machine learning techniques used by firms such as Google or Facebook
  • Face detection with OpenCV
  • TensorFlow

 

Requirements:

  • Basic python

Description:

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.

  • Machine Learning Algorithms: regression and classification problems with Linear Regression, Logistic Regression, Naive Bayes Classifier, kNN algorithm, Support Vector Machines (SVMs) and Decision Trees

  • Machine Learning approaches in finance: how to use learning algorithms to predict stock prices

  • Computer Vision and Face Detection with OpenCV

  • Neural Networks: what are feed-forward neural networks and why are they useful

  • Deep Learning: Recurrent Neural Networks and Convolutional Neural Networks and their applications such as sentiment analysis or stock prices forecast

  • Reinforcement Learning: Markov Decision processes (MDPs) and Q-learning

Thanks for joining the course, let's get started!

Who this course is for:

Course Details:

  • 18.5 hours on-demand video
  • 9 articles
  • 1 downloadable resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of completion

Introduction to Machine Learning & Deep Learning in Python udemy courses free download

Regression, Naive Bayes Classifier, Support Vector Machines, Random Forest Classifier and Deep Neural Networks

Demo Link: https://www.udemy.com/course/introduction-to-machine-learning-in-python/

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