Free good sources to learn Machine Learning

In this article I will list out the useful sources from where you can learn more about Machine Learning. Before that just to revise take a look at introduction to Machine Learning:

About ML

What is Machine Learning?

In simple language we need to create and train the ML model. We give it inputs and corresponding outputs and machine or computer will learn how to map the input to the corresponding output during the training for example classify cat in the image as a cat. When model shows desired results in the mapping with satisfying accuracy we say model is ready to use.

How ML model development looks like?

Generally in Machine Learning projects after data extraction and pre-processing it can be seen that it is normally divided into two different phases: Model creation (where we train the model using training data that we have) and after that use the trained model in actual production (on the new incoming data).

Dig: depiction of General Machine Learning Model development and deployment

Note that model development is an iterative process that means with time and arrival of new data based on the results of the existing model we need to optimise our existing model by different methods to create new more accurate model if need arises.

Now we can go through some of the good and useful sources which are free and accessible to all using internet to know more about Machine Learning:

Coursera

Following course is good to start with

1. Machine Learning by Stanford (Andrew Ng)

There are many useful courses on the Coursera which you can audit free of cost or can pay for the certification (Also Coursera offers financial aid).

YouTube Channels

There are lots of useful Youtube channels as of now some of the famous channels are: Siraj Rawal, Data School, sentdex, etc similarly you can search for more channels and subscribe to them to learn more free of cost.

Sharing: introductory lecture on AI: Data Lit (Official Music Video) by Siraj Rawal 🙂

Kaggle

On Kaggle you can Learn the Problems and ML Solutions accepted to solve them. This will give you some idea how to apply ML solutions to the real world problems.

1. Kaggle – Learn Machine Learning

2. Kaggle – Introduction to Machine Learning

3. Kaggle Machine Learning Competitions

StackOverflow:

At the time of program execution if find any issues or errors you can ask or check answers on the StackOverflow.

(You can also check my answers on the Stack overflow: link 🙂

Other sources:

Also there are other sources that you can refer such as

1. Books

2. Blogs, websites

3. Courses in Edx, Udemy, etc

4. Which are the best online courses for machine learning?

You can refer them as per your requirements with time.

These are some of the sources that I find very useful to learn more about Machine Learning by my self. But above mentioned sources are not the final list and you can expand or find other sources as well depending upon your own interest and content that you want to learn.