IT & Software

[FREE]Machine Learning (ML) Bootcamp: Python, TensorFlow, Colab

Do you want to master Machine Learning (ML) – the key field of the future?

ML is the core of artificial intelligence and will transform all industries and all areas of life.

This comprehensive course covers the three M’s Maths, Methods and Machine, and is easy to understand.


  • Calculus
  • Linear Algebra
  • Probability theory
  • Statistics


  • Machine learning libraries
    • Scikit-learn
    • Tensorflow
    • Keras
  • Estimators & Predictors
    • Neural Network (Deep Learning)
    • Support Vector Machine
    • K-Nearest Neighbor
    • Decision Tree
    • and many more
  • Concepts & techniques
    • Principal Component Analysis (PCA)
    • Neural Machine Translation (NMT)
    • Long Short-Term Memory (LSTM)
    • Monte-Carlo Tree Search (MCTS)
    • Deep Convolutional Generative Adversarial Network (DCGAN)
    • and many more


  • Python
  • Cloud Computing
  • Colab Cloud Notebook

These three building blocks will give you the deep understanding of the subject.

Machine Learning

  • Supervised learning
    • Regression
    • Classification
  • Unsupervised learning
  • Reinforcement learning

Furthermore projects will provide insights into real life solutions.


  1. Titanic dataset (binary classification)
  2. Boston Housing dataset (regression)
  3. Student performance (binary classification)
  4. Hand-written digits (image recognition & generation)
  5. Stock market predictions
  6. Text recognition and language translation
  7. Autonomous driving (reinforcement learning)
  8. Mastering the game of GO (deep reinforcement learning)
  9. Segmentation of customer data (PCA)
  10. Spam detection (Bayes)

Do not hesitate and join the course. ML will transform your life!

This course is extraordinary, as it is easy to understand, and combines education with entertainment.

Learning should be exciting!

What you’ll learn

  • The three building blocks of Machine Learning: Maths, Methods and Machine.
  • Maths: Calculus, Linear Algebra, Statistics, Naive Bayes
  • Methods: Neural Networks, Deep Learning, PCA, Scikit-learn, Tensorflow, Keras
  • Machine: Python, Cloud Computing, Colab
  • Insights into real life projects and how to apply the concepts

Also Check:- [FREE]Python for Machine Learning bootcamp (20 Hrs)


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