Hands on Machine Learning with Python Course Online | infyni

Hands-on ML using Python

Hands-on ML using Python trains you to apply the best machine learning practices using all the powerful features of Python. Our instructors are AI ML experts from the industry who train you hands-on for real-life scenarios. You will learn the latest ML trends in this course.

Live Course

Live Class: Friday, 08 Mar

Duration: 45 Hours

Enrolled: 12

Offered by: infyni


Live Course
$650 20% off


About Course

Hands-on ML using Python is a comprehensive course on machine learning. It explains the basic statistics and programming that are required to work on machine learning problems. The course explains the basics of Python programming and the various packages required for machine learning. It also covers statistical distributions and explains the various types of data you will need to work with.

The course then teaches you a type of machine learning called reinforcement learning. Reinforcement learning has applications in game development, smart assistants, recommendation systems, and in industries as varied as finance, oil and gas, etc. The course will explain reinforcement learning using a real world case study to ensure that learning is practical and hands-on.

Skills You Will Gain

Logistic Regression Natural Language Processing Machine Learning (ML) Algorithms Machine Learning Decision Trees RNN CNN GANs

Course Offerings

  • Instructor-led interactive classes
  • Clarify your doubts during class
  • Access recordings of the class
  • Attend on mobile or tablet
  • Live projects to practice
  • Case studies to learn from
  • Lifetime mentorship support
  • Industry specific curriculum
  • Certificate of completion
  • Employability opportunity
  • Topics
  • Instructor (1)
  • Reviews
  • Fundamentals of ML
  • ML Landscape
  • End-to-End ML Project
  • Classification
  • Training Models
  • SVM
  • Decision Trees
  • Ensemble Learning and Random Forests
  • Dimensionality Reduction
  • Unsupervised Learning techniques
  • Custom models and training with TensorFlow
  • Loading and Preprocessing data with TF
  • Deep Computer Vision using CNN
  • Processing Sequences using RNN and CNN
  • NLP with RNN
  • GANs
  • Reinforcement learning
  • Hands-on Live Projects