Here’s Shubhamai journey of how I get started with nothing and in just a year and a half, I become a complete Machine Learning Engineer, with knowledge of Machine Learning, Deep Learning, Computer Vision and Natural Language Processing, and much much more!
I just started with a laptop and courage to learn something, like programming, I love Robotics & Space, so I research a bit for what programming language if good for them, turns out, this was hard, I was overwhelmed by such many programming languages, but one of them get into my line of sight, Python. So, I started my journey — —
Python (September 2018 — March 2019)
I started, to be truthful, 90% of python I learn was from many many Youtube Videos, who teach me many different kinds of stuff —
I love this course because it was my first ever Programming Course,
The instructor was AWESOME. Also, these playlists were very powerful
I learned a lot with these below playlists, I didn’t see all of the videos, but an important one
And many many other Youtube video, I can’t list all of them sorry,
and I also do a single course from Udemy which was this
I learned a lot of many things in this course and overall, it was a very good course, not wonderful to be truthful, because many things are out of interest for me, like Sqlite, (I am a bit biased 😄).
Machine Learning (April 2019 — May 2019)
I research many days for my dream course for Machine Learning and I saw this — —
Machine Learning A-Z (Python & R in Data Science Course)
This was wonderful, I will admire this that this course has so powerful and so great, I learned so many things that I can’t even list them here.
Deep Learning (May 2019 June 2019)
Super Data Science is in my hearts still today, because I have learned so many things with their courses, and this deep learning is no exception, ANN, CNN, RNN, LSTM, Self Organising Maps, Deep Boltzmann Machines, and Variations Autoencoders, and much more…. I don’t know what to say!
Projects Session (June 2019 — July 2019)
I do many projects in this 2 months project session, projects are very important, I learned a lot of things by experimenting with new things, working on kaggle competitions.
Computer Vision (July 2019 — August 2019)
This was one of the most exciting courses for me because I love robotics, I love computer vision. Nowadays, I work daily with computer vision, I have also written 1 documentary of one of my computer vision projects here — —
Object Detection with Detectron2
and another one which I am working on currently, I much much bigger than this, back to the work, so in this course, I learned the basics of computer vision, face detection, smile detection, ear nose, you guess, and Object Detection and finally Generative Adversarial Networks to generate fake images, this was a mind-blowing one.
Natural Language Processing (September 2019 — October 2019)
This course was one of the hardest courses for me to understand, I don’t like NLP very much, I even rarely touch NLP, but I saw that I will make a chatbot so to take the course. I learned Seq2Seq, Attention Mechanisms, Bag of Words, and the best part, making Chatbot for scratch.
Turns out, it was very boring and very hard for me to make chatbot from my own so sadly, I leave the course uncompleted, but still, I learned a lot of the fundamentals and learned a lot of things.
Project Session (October 2019 — November 2019)
It’s not like I do projects only on project sessions, but I have done many projects while learning the courses, but this session, I build one of my biggest project — —
It was very fun all it was actually computer vision projects, I implement a lot of new things like hawk eye, which was an absolute AMAZING thing for me
Getting up Upgrade (November 2019 — December 2019)
I learned a lot of practical skills, but I was sure that I lack theoretical skills of Machine Learning, especially Deep Learning and Neural Networks, and other stuff like Linear Algebra and Calculus, so this month, I committed to working very hard to fill up these gaps in my skills, so I did these many courses —
Course Machine Learning & Deep Learning Courses From Andrew Ng —
Andrew Ng is one of the best teachers I have ever seen, he teaches stuff in very simple language and then slowly teaches advanced stuff, and I still learned a lot of things in this course, like fundamental maths for machine learning, and many regularization techniques, learning rate schedules, large scale machine learning, sequence models, GRU and much much more…..
I don’t know why, but the teaches who teaches me Linear Algebra of Khan Academy is an absolute legend for me, he teaches the subject in a way that, it looks like learning linear algebra and calculus is like eating a piece of cake 🍰
And the second link, was also a course for Mathematics for Machine Learning, it was going very well good in linear algebra but in calculus part, I gave up, I couldn’t able to understand anything in that one. So I did these —
Grant Sanderson, the creator of 3Blue1Brown Youtube channel for Math, I don’t need to say any words for him, everyone knows that his style to teach math is infinitely AWESOME and his visualizations like spoke out the screen,
His two of the series one for Linear Algebra and Calculus, my all doubts were clear and I understand everything of Linear Algebra and Calculus, so let’s go
But this wasn’t enough
Yes, it is, now I got the confidence that I know the mathematics for Machine Learning, I still lack how neural networks work under the hood, but all of them were crystal clear after seeing this series.
Python & Machine Learning Revision
Now, I understand everything I should, I saw ZeroToMastery for the first time, and to be truthful, I fell love with it. Andrei teaching and his courses are filled with so so much knowledge, that still after working with python for more than a year, I saw that it was a lot of lot more to learn
I learn decorators, and for the first time, I clearly understand classes in python, generators, testing in python, regex, a career in python, web scraping, API, Web Development, Flask, Selenium, and much much more…..
In January 2020, ZeroToMastery also publish another course, now there was another instructor Daniel Bourke, (which is now my best friend ever from another country!), Machine Learning and before purchasing, when I see the contents, my mind blew up 🤯, I just take the course — —
Complete Machine Learning and Data Science: Zero to Mastery
I learned, Data Engineering, working with tf.data , ROC, AUC, storytelling and communication, data manipulation techniques, and a lot more things...
Web Development (February 2020 — March 2020)
I also want to learn web development, just because my mind said like that, and my mood was in the line of sight of web development, so an again took one of the ZeroToMastery courses
The Complete Web Developer in 2020: Zero to Mastery
March 2020 — Now
Projects, Projects, Projects, still now I am working on just projects, I am putting my soul in one of the Kaggle Competitions and making a documentary for that, I learned a lot of my past 2 kaggle competitions of this year, which were both computer vision projects.
Do you still remember, I love robot & space, guess what is the other important field of machine learning for robotics —Deep Reinforcement Learning,
My goal from June 2020 — January 2021 is to learn Deep Reinforcement Learning very very deeply, Understand every part of it and in the next year 2021, guess what, making robots, drones, rockets, powered by AI, Computer Vision, Deep Reinforcement Learning, maybe NLP, joining everything that I am learning for past 2 years.
Other than the course and projects, there are hundreds of blogs and videos i have seen from great writers who post their beautiful work in the world for FREE
Do not repeat my mistakes
Yep, in this long journey, I have done many mistakes, many of them, and if you are getting in ML, this is the path I would suggest you master this vast field.
To be truthful, if this course was available when I started learning Python, I wouldn’t have to spend 6 months learning every bit of python and still left many things which I learned in this course.
- Machine Learning & Data Science
Complete Machine Learning and Data Science: Zero to Mastery
If anyone will ask me how to get started with ML, my first sentence will be Take Complete Machine Learning & Data Science course from ZeroToMastery in Udemy. This course really set up a great great fundamental for Data Science, Machine learning, and all-powerful libraries used in Machine Learning like pandas, numpy, matplotlib, scikit-learn, TensorFlow, Keras, and other stuff like neural networks, data engineering, storytelling, and communication just to name a few.
- Machine Learning Maths
Neural Networks Under the Hood —
Same here, if anyone will say I don’t know maths for ML, here’s the deal. Now it is time to increase more knowledge of Machine Learning Maths, and this series will start from basics and teaches you with soo cool visualizations, you will learn everything you need to learn ML maths.
- Getting Advanced
Advanced Machine Learning — https://www.coursera.org/learn/machine-learning?)
Advanced Deep Learning & Computer Vision — https://www.coursera.org/specializations/deep-learning?)
Now it's time to get advanced, these two courses will do that for you. There will be so many new things to learn in these two courses that I can't list here.
- Machine Learning (The Big Picture)
You have to know what truly is AI, Machine Learning, in the Big Picture, why the world needs AI in this generation so much, also why this age is class the Machine Revolution, all the answers are here below. And also a lot of motivation for how far you have come.