**NODES, The Dev Community Conference by Neo4j!**

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by Arbaaz SiddiquiJune 19th, 2020

This post covers all you will need for your Journey as a Beginner. All the Resources are provided with links. You just need Time and Your dedication.

**I have separated this post into several programs as shown below:**

- Path A. 4 to 5 Months
- Path B. 2 Months or Less
- Path C. 1 Month or Less

**Part 1: Start With Machine Learning, 2 months.**

- Machine Learning course by Stanford University (
)**coursera.org/learn/machine-learning** - By the time you start Neural Network on week 5 at the Coursera course, complete the Neural Networks playlist by
*3BIue1Brown**.* - I think the Coursera course rushes the Neural Network part a little bit, there is a fantastic free online book on
**Neural Network**and**Deep Learning**()*neuralnetworkanddeeplearning.com* - Now many of the concepts in Machine Learning and Deep Learning literature will start making sense to you. For fun, head over to
**Chriss Olah’s blogs**, they’re awesome! ()*http://colah.github.io/*

**Part 2: Deep Learning, 1 month.**

- Before you start Deep Learning, you need to brush up some university math.
**The Deep Learning Book***by*, I would recommend you go through*Ian Goodfellow***Linear Algebra**and**Probability**and**Information****Theory**chapters as deeply as you can. - My best pick to start Deep Learning is with
**Andrew Ng’**s Deep Learning specialization. (*c*)*oursera.org/specializations/deep-learning* - It’s also time to read Chapter 3, 4, 5, 6 from
to strengthen your concepts*neuralnetworkanddeeplearning.com*

**Timing**: if you are working full time on these courses, l think it’s possible to finish each week’s content in **1~2 **days. So don’t get intimidated by

the schedule. But give yourself some time to **breathe between courses**.

**Part 3: Practical Implementation of Deep Learning (1~2 months).**

**Fast.ai** has a wonderful resource for practical Deep Learning (* course.fast.ai*), While Andrew Ng or others teach in a

Complete the first 5 weeks of the** Machine Learning course from Coursera**, Do the programming exercises.

- Watch the
*Neural Network**playlist*from**3Blue1Brown**youtube channel. - Complete Course (
*Neural Networks*and*Deep Learning*) from**Deep Learning Specialization**in. Do the exercises.*Coursera* - if you want to start an
**Image Processing project**, take the 4th-course ln Coursera specialization or if you want to work on**Natural Language Processing**or**sequence data**, take course no.5.

Search for open source implementation and YouTube videos of projects that you are interested in. if you are concerned about which language to use, I think it’s good to stay with *Keras **(*** Keras is an open-source neural network library written in Python**)

*Skim*through Coursera**Machine Learning**course Week 1 to 5. Just watch the videos, grasp the concept. You can*skip the MATLAB/Octave*tutorials in Week 3.- Watch the Neural Network playlist from
**3Blue1Brown**youtube channel. - Skim through Course (Neural Networks and Deep Learning) from Deep
**Learning Specialization***in***Coursera**. - If you want to do an
**Image Processing projec**t read the chapters from**Nielsen’s book:****neuralnetworksanddeeplearning.com/chap6.html** **Siraj Raval**has some interesting videos to give you a gist of most**ML**and**DL**topics.

*Search for open source implementation and YouTube videos of projects that you are interested in. And keep tweaking them to your need*

**Neural Networks and Deep Learning:****coursera.org/learn/neural-networks-deep-learning**

**Sequence Modeling-****colah.github.io/posts/2OI5–08-Unndersting-LSTMs/**

**Siraj Raval**: **Youtube Channel**

I would suggest you to follow **2 minutes Paper** on YouTube to get

updated with the wonders that researchers are doing with Deep Leaning around the world.

*Previously published at **https://medium.com/@arbaazsama/machine-learning-101-how-where-to-start-for-absolute-beginners-59e790c92c50*

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