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 Path A: Learn In 4 to 5 Months. 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 and ( ) Neural Network 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 , they’re awesome! ( ) Chriss Olah’s blogs http://colah.github.io/ Part 2: Deep Learning, 1 month. Before you start Deep Learning, you need to brush up some university math. , I would recommend you go through and and chapters as deeply as you can. The Deep Learning Book by Ian Goodfellow Linear Algebra Probability Information Theory My best pick to start Deep Learning is with s Deep Learning specialization. ( ) Andrew Ng’ c oursera.org/specializations/deep-learning It’s also time to read Chapter 3, 4, 5, 6 from to strengthen your concepts neuralnetworkanddeeplearning.com : if you are working full time on these courses, l think it’s possible to finish each week’s content in days. So don’t get intimidated by the schedule. But give yourself some time to . Timing 1~2 breathe between courses Part 3: Practical Implementation of Deep Learning (1~2 months). has a wonderful resource for practical Deep Learning ( ), While Andrew Ng or others teach in a (know first, do later) fast.ai teaches in a (do first, know later).Two other courses I would mention is and . is focused on computer vision with Deep Learning, and focuses on Sequence Modeling such as Natural Language Processing with Deep Learning. Fast.ai course.fast.ai Top-down approach bottom-up approach CS231n CS224n by Stanford University CS231n CS224n Path B: Learn in 2 Months or Less. Complete the first 5 weeks of the , Do the programming exercises. Machine Learning course from Coursera Watch the from youtube channel. Neural Network playlist 3Blue1Brown Complete Course ( and ) from in . Do the exercises. Neural Networks Deep Learning Deep Learning Specialization Coursera if you want to start an , take the 4th-course ln Coursera specialization or if you want to work on or , take course no.5. Image Processing project Natural Language Processing sequence data 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 Path C: Learn in 1 Month or Less. through Coursera course Week 1 to 5. Just watch the videos, grasp the concept. You can tutorials in Week 3. Skim Machine Learning skip the MATLAB/Octave Watch the Neural Network playlist from youtube channel. 3Blue1Brown Skim through Course (Neural Networks and Deep Learning) from Deep . Learning Specialization in Coursera If you want to do an t read the chapters from Image Processing projec Nielsen’s book: neuralnetworksanddeeplearning.com/chap6.html has some interesting videos to give you a gist of most and topics. Siraj Raval ML DL Search for open source implementation and YouTube videos of projects that you are interested in. And keep tweaking them to your need Links & Optional Resources. 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 on YouTube to get updated with the wonders that researchers are doing with Deep Leaning around the world. 2 minutes Paper Previously published at https://medium.com/@arbaazsama/machine-learning-101-how-where-to-start-for-absolute-beginners-59e790c92c50
