I am starting 100 Days of ML Challenge to push myself out of my comfort zone and to level up my knowledge in Machine Learning.
Day 0: 22 June, 2020 Today's Progress: Today I tried to have a rough roadmap to how I will go on with my 100 Days.
Thoughts: Creating a roadmap is not as easy as it seems, there are many things to learn and know. Machine learning is a vast field and it has many roles in it. I also got to know that Machine learning engineer, data scientist, data engineer are just some of the many roles.
- Data Bootstrap skills (or) Data science literacy - I will learn what is data, how is it generated, how to analyse it, how to get insights from it and how it can benefit the overall flow of events.
- Information Design and Presentation - I will learn how to present data and insights so that the relevant person can be benefitted from it.
- Statistics and Machine learning - I will learn statistics and machine learning, this will be a new experience for me as I am not an expert in either.
- Deep programming - I will learn various frameworks and languages needed to achieve my goal.
- Domain expertise - I will try various domains then decide where to have expertise. See Inspiration
Day 1: 23 June, 2020 Today's Progress: Today I refreshed my knowledge of linear algebra, coding using linear algebra was something I did for the very first time.
Thoughts: I thought that today I would be able to complete linear algebra, calculus and probability all together just because I have read it before but I was wrong. Filling the gaps and revising takes a lot of time. I was able to complete linear algebra today and use it to code also, I learnt python fuctions to find inverse. I am following this course from coursera as my guide, also 3Blue1Brown Linear Algebra
Day 2: 24 June, 2020 Today's Progress: Today I refreshed my knowledge of multivariable calculus.
Thoughts: It might take a week to complete calculus as well as probability. I will try to end calculus as soon as posible.
Day 3: 25 June, 2020 Today's Progress: Today I refreshed my knowledge of multivariable calculus. Learnt that classical techniques focuses on repetition to understand, when we are using computer we need to understand and then the computer can do the heavy lifting for us.
Thoughts: I did not update the progress yesterday on github so it is showing a day gap, I don't feel good about it but I tweeted about my day and also studied chain rule, product rule and others. I am feeling good about this 100 day challenge, even though it has been only 3 days (not 4th day as I am writing this on 26th june) the outcome will be very good.
Day 4: 26 June, 2020 Today's Progress: I completed the Linear Algebra and Multivariable calculus today. Will be starting with Principle component analysis and Probability from tomorrow.
Thoughts: Mathematics if the fundamental of everything and its knowledge is very important. I am taking time to understand the concepts and topics, covering gaps and revising everything. This Cheatsheet is very helpful
Day 5: 27 June, 2020 Today's Progress: I coded a basic machine learning model using Random forest and Decision tree and completed intro to Machine learning from kaggle.
Thoughts: The computer is just like a baby very good at maths. It is dumb and smart at the same time. I will be focusing on Stock market prediction going forward as I have no interest in computer vision and always wanted to learn to predict the stock market.
Day 6: 28 June, 2020 Today's Progress: I looked for what learning is, its types and why do we even need Machine learning in the first place.
Thoughts: Data science is a pandora's box. It just contains too many things.
Day 7: 29 June, 2020 Today's Progress: I completed kaggle courses and now starting to shift gradually from theory to algorithms as best way to learn is by doing.
Thoughts: I am liking the flow in which things are moving forward. I am happy that I choose 100 day challenge as it helps in building consistancy.
Day 8: 30 June, 2020 Today's Progress: I completed the Carsh course AI on youtube
Day 9: 1 July, 2020 Today's Progress: I completed till chapter 10 in Understanding Machine learning from theory to algorithms - by Shai Shalev Shwartz and Shai Ben David.
Day 10: 2 July, 2020 Today's Progress: I crash course statistics on youtube today.
Day 11: 3 July, 2020 Today's Progress: Today I was feeling a bit burnout so I revised the things I have studied and Solved problems on HackerRank.
Day 12: 4 July, 2020 Today's Progress: Right now I am reading "Introduction to Machine learning by Ethem Alpaydin"
Day 13: 5 July, 2020 Today's Progress: Right now I am reading "Introduction to Machine learning by Ethem Alpaydin"
Day 14: 6 July, 2020 Today's Progress: Right now I am reading "Introduction to Machine learning by Ethem Alpaydin"
Day 15: 7 July, 2020 Today's Progress: Right now I am reading "Introduction to Machine learning by Ethem Alpaydin"
Day 16: 8 July, 2020 Today's Progress: Right now I am reading "Introduction to Machine learning by Ethem Alpaydin"
Day 17: 9 July, 2020 Today's Progress: Right now I am reading "Introduction to Machine learning by Ethem Alpaydin"
Day 18: 10 July, 2020 Today's Progress: Right now I am reading "Introduction to Machine learning by Ethem Alpaydin"
Day 19: 11 July, 2020 Today's Progress: I did Hackerrank problems today.
Day 20: 12 July, 2020 Today's Progress: https://github.com/academic/awesome-datascience#competitions This is a truly great resource
Day 21: 13 July, 2020 Today's Progress: Reading "Artificial Inteliigence Structure and Strategies for Complex Problem Solving by George F Luger" Chapter 1
Day 22: 14 July, 2020 Today's Progress: Reading "Artificial Inteliigence Structure and Strategies for Complex Problem Solving by George F Luger" Chapter 2
Day 23: 15 July, 2020 Today's Progress: Reading "Artificial Inteliigence Structure and Strategies for Complex Problem Solving by George F Luger" Chapter 3