These are good resources I have found to learn yourself Machine Learning, Deep Learning and other AI subjects.
There are free and paid courses and different levels.
Divided into short courses (from 1 to 20 hours ). These are courses to take a first contact with the subject
- Intro to Machine Learning by Kaggle Short, only 3 hours
- Machine Learning Crash Course by Google with TensorFlow APIs (15 hours)
- Intro to Deep Learning by Kaggle 4 hours to learn DL and TensorFlow. Learn the core ideas in machine learning and build your first models.
- Stanford Classes IA vision a youtube channel list with Stanford classes to learn about IA vision computer (20 hours)
- Introduction to Deep Learning by MIT. It is only for graduates or old-graduates but we can see an list the videos of classes.
- Elements of AI. A free online introduction to artificial intelligence for non-experts by TheUniversity of Helsinki.
From begginer to Advanced
- Machine Learning by Andrew ng Probably the most known and old course of ML. I studied and passed this course last year. It is very theoretical, You learn basis an how ML works, but I think it needs more practical weight. (Here my review)
- Course fast AI by fast.ai
- Intermediate Machine Learning by Kaggle is de continuation of the begginer course. Learn to handle missing values, non-numeric values, data leakage and more. Your models will be more accurate and useful
- Deep Learning by Google (3 months) (Intermediate to advanced level) Developed by Audacity with Vincent Vanhoucke, Principal Scientist at Google, and technical lead in the Google Brain team.
Perhaps the best one to learn Deep Learning and Machine Learning
- Deep Learning Specialization by Deep Learnin AI – Deep Learning Specialization. Master Deep Learning, and Break into AI. The specialization courses by Andrew Ng to learn DL. It is a paid course formed by a 5 you paid $40 each month until you finish them (aprox 3 months – 11 hours/week suggested). The five courses are:
- Neural Networks and Deep Learning
- Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
- Structuring Machine Learning Projects
- Convolutional Neural Networks
- Sequence Models
- Kaggle Competitions This is one of the best ways to learn and to practice what you are learning.
And to complete information and resources about Artificial Intelligence and
Python for Data Science
One of the main skills to learn ML, DL or AI is to know Python. There are other languages but this is the most common and used in Data Science
In Kaggle you can find one little course with basic principles.
I will continue updating this list with more things as I find them. If you know something, comment please.