Machine Learning (Full Course)

This app is an excellent choice for beginners to learn machine learning & artificial intelligence (AI) through interactive video tutorials and lessons for free. Also, this app doesn't require any signup process which makes it extremely user-friendly and convenient to use.

★ What you'll learn in this course? ★

1. Master Machine Learning, become a Data Scientist and get hired

2. Build an army of powerful Machine Learning models and know how to combine them to solve any problem

3. Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0

4. Use modern tools that big tech companies like Google, Apple, Amazon and Meta use

5. Present Data Science projects to management and stakeholders

6. Learn which Machine Learning model to choose for each type of problem

7. Real life case studies and projects to understand how things are done in the real world

8. Learn best practices when it comes to Data Science Workflow

9. Implement Machine Learning algorithms

10. Learn how to program in Python using the latest Python 3

11. How to improve your Machine Learning Models

12. Learn to pre process data, clean data, and analyze large data.

13. Developer Environment setup for Data Science and Machine Learning

14. Machine Learning on Time Series data

15. Explore large datasets using data visualization tools like Matplotlib and Seaborn

16. Explore large datasets and wrangle data using Pandas

17. Learn NumPy and how it is used in Machine Learning

18. A portfolio of Data Science and Machine Learning projects to apply for jobs in the industry with all code and notebooks provided

19. Learn to use the popular library Scikit-learn in your projects

20. Learn about Data Engineering and how tools like Hadoop, Spark and Kafka are used in the industry

21. Learn to perform Classification and Regression modelling

22. Build artificial neural networks with Tensorflow and Keras

23. Implement machine learning at massive scale with Apache Spark's MLLib

24. Classify images, data, and sentiments using deep learning

25. Make predictions using linear regression, polynomial regression, and multivariate regression

26. Data Visualization with MatPlotLib and Seaborn

27. Understand reinforcement learning - and how to build a Pac-Man bot

28. Classify data using K-Means clustering, Support Vector Machines (SVM), KNN, Decision Trees, Naive Bayes, and PCA

29. Build a movie recommender system using item-based and user-based collaborative filtering

30. Use data science algorithms to analyse data in real life projects such as spam classification and image recognition

31. Build a portfolio of data science projects to apply for jobs in the industry

32. Understand how to use the latest tools in data science, including Tensorflow, Matplotlib, Numpy.

33. Create your own neural networks and understand how to use them to perform deep learning

34. Understand and apply data visualisation techniques to explore large datasets

35. Genuinely understand what Computer Science, Algorithms, Programming, Data, Big Data, Artificial Intelligence, Machine Learning, and Data Science is.

36. To understand how these different domains fit together, how they are different, and how to avoid the marketing fluff.

37. The Impacts Machine Learning and Data Science is having on society.

38. To really understand computer technology has changed the world, with an appreciation of scale.

39. To know what problems Machine Learning can solve, and how the Machine Learning Process works.

40. How to avoid problems with Machine Learning, to successfully implement it without losing your mind!

★ Disclaimer ★

Developer claims no credit for any video embedded in this app unless otherwise noted. Videos embedded in this app are copyright to its respectful owners. If there is an video appearing in this app that belongs to you and you do not want it to appear in this app, please contact us via email and it will be promptly removed.

★ Icon Credit ★

https://www.flaticon.com/free-icons/machine-learning