1/ 🧵 Getting started with data science and machine learning.
- the first step is to know what data science and machine learning mean and is this field worth getting into?
- if you ask me, I would say yes. the world is data-centric.
- the first step is to know what data science and machine learning mean and is this field worth getting into?
- if you ask me, I would say yes. the world is data-centric.
2/ in every industry, data is useful and will be for a long long time.
- if you are a developer, it will be easier for you to get into data science
- but it also means you have to work twice as hard since you are already working
- if you are a developer, it will be easier for you to get into data science
- but it also means you have to work twice as hard since you are already working
3/ - if you are a fresher or a student, it's much easier for you to spend at least 4 hours a day learning something new
- now a lot of people ask where to start from?
- step 0 will be learning to code.
- now a lot of people ask where to start from?
- step 0 will be learning to code.
4/ I prefer python and so does the majority of the industry and research when it comes to machine learning/data science
- then, you can start by googling what is machine learning and reading the Wikipedia page.
- then, you can start by googling what is machine learning and reading the Wikipedia page.
5/ then you can try Andrew Ng's Coursera course on machine learning and create an account on Kaggle. Go through the course, work out the exercises and simultaneously, start taking part in a Kaggle competition: for example, the Titanic one.
6/ Also, there is no need to spend more than a few weeks (max 1 month) on this competition.
- a lot of people will tell you that you don't need to know the basics, just learn very high-level libraries, but do not trust them.
- a lot of people will tell you that you don't need to know the basics, just learn very high-level libraries, but do not trust them.
7/ start from the course mentioned above but do solve a problem simultaneously.
- These are a few courses you can take a look at:
- These are a few courses you can take a look at:
8/ Coursera machine learning: coursera.org/learn/machine-…
10/ CS229 Machine Learning:
11/ Intro to convnets (CS231n):
12/ Natural Language Processing with deep learning (CS224n):
14/ Machine learning crash course from google: developers.google.com/machine-learni…
15/ to be honest, there are many free courses available online that you can go through. it doesn't matter which courses you take. if you plan on just starting a course and solving problems without understanding anything, you will be in big trouble.
16/ if you do not plan on finishing a course, it's better not to start.
If you plan to do MSc, there are many universities that offer degrees in computer science and data science, ai, etc in both Europe and the USA. P.S. in Europe, most universities do not have a tuition fee.
If you plan to do MSc, there are many universities that offer degrees in computer science and data science, ai, etc in both Europe and the USA. P.S. in Europe, most universities do not have a tuition fee.
17/ Unfortunately, I don't advise on which universities to go for. All universities are good. It's all up to the student.
18/ In short, start from courses, join Kaggle and do 101 competitions, in the beginning, come up with nice projects for your portfolio, write good quality blogs and articles, do not copy-paste, rather, understand and implement on your own and jump into Kaggle competitions with…
19/ …prize money for advanced learning. if you don't understand something, there are many channels where you can ask questions: StackOverflow, Kaggle discussions, and even on Twitter!
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