when I started out, I knew nobody that worked or had knowledge of Data Science which made me try all sorts of different things that were not actually necessary.
You are looking to get into Machine Learning? You most certainly can
Because I believe that if an above-average student like me was able to do it, you all certainly can as well
Here's how I went from knowing nothing about programming to someone working in Data Science👇
when I started out, I knew nobody that worked or had knowledge of Data Science which made me try all sorts of different things that were not actually necessary.
I learned it out of curiosity and I had no idea about Machine Learning at this point.
The approach I took was just to make the same kind of programs I made in C but just replacing the syntax with that of python and practised those.
Already knowing a language made it easier.
I didn't have to have any idea about Machine Learning for the course. I completed that in almost a month and it gave me a good intuition of things and the flow of ML.
But after a lot of tries, I wasn't really able to do it. Because I was constantly encountering a lot of stuff things in code that I wasn't really aware of.
Even loading the CSV data seemed like a hard task.
The absolute necessary ones were
🔸Numpy
🔸Pandas
🔸Matplotlib
🔸Seaborn
🔸SciKit Learn
🔸Os (an important built-in package).
The practice of the taught concepts multiple times was necessary, I did that as much as I could and also read blogs on them
Different people solve the same problem differently and you read a lot of other people's code. From there on that's what kept me growing.
🔹Exploration and visualization of data
🔹How to approach a new problem
🔹Better code structure for implementing a machine learning solution
You don't have to be an absolute grandmaster of kaggle but plenty practice and patience is needed.
▪ Titanic Survival
▪ Spam Classification
▪ Movies Recommendation
▪ Boston House Pricing
▪ Churn Prediction
You'll kind of know your way from there, moving to harder problems slowly.
Learning the maths behind will keep things interesting if you won't enjoy that you will get bored pretty quickly.
And you are NOT too old or too young for this stuff
Look at these two guys @svpino @PrasoonPratham !
I am listing the resources below. These are what I used, they don't have to be the same, see what works for you better. Bend things your way.
More from Coding
Thread 🧵👇🏻
1⃣ https://t.co/H2sKWKEeaz
- Learn DSA and visualize some complex programs. Definitely check it out.
2️⃣ https://t.co/0WcFTWBfh9
- Dedicated to graph DS
3️⃣ https://t.co/ShEQQkjtWD
- Visualizing data structures and algorithms through animation
4️⃣ https://t.co/XxzwBa3vvZ
- All sorting algorithms animations
Here's a list of websites to get inspiration for design and building UI:
🧵👇🏻
1. Behance
https://t.co/eNm9PHPwiv
2. Dribbble
https://t.co/79Zq4AISuB
3. Httpster
https://t.co/U7xXszEdRU
4.
5. Design Notes
https://t.co/io8DVOLWSv
6. Land Book
https://t.co/KsNQxWxmqh
7. Frontend Mentor
https://t.co/NfvVVgEsOE
8.
9. Codrops
https://t.co/hfmwzhG0bk
10. SaaS Landing Page
https://t.co/NYXxCvFDTj
11. Pages .xyz
https://t.co/ilxtaHQ7j5
12. UI
13. lapa ninja
https://t.co/nmhJ6wgSfl
14. Freefrontend
https://t.co/FrDYMKfnPO
15. Webframe
https://t.co/GhVhkWFg5f
16. Collect
A Master Thread 👇🏽
Table of Contents:
- Illustrations
- Development
- CSS
- Tailwind
- Design
- Productivity
Illustrations
1. Drawkit (https://t.co/Lx4TeeHZ2G)
2. Blush (https://t.co/FDlRDK9J2M)
3. Smash illustration (https://t.co/v7EQXb4se8)
4. Control (https://t.co/e9tEQmURjG)
5. Error 404 (https://t.co/6zW1nTIw63)
6. Open Doodles
Development
1. Carbon (https://t.co/gDNwi0FvLu)
2. Squoosh (https://t.co/g39cY2PEtH)
3. Wappalyzer (https://t.co/kVXz18fgjX)
4. Kite (https://t.co/PrpSxs0rgK)
5. DevHints (https://t.co/SbBuOZ2ibh)
6. iHateRegex (https://t.co/BJgd1pOlni)
7. DevDocs
CSS
1. Animista (https://t.co/FrW6TyvspG)
2. Pattern.css (https://t.co/5Va3WHNo5U)
3. CSSeffectsSnippets (https://t.co/XlWUD1m6V2)
4. 98.css
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Covering one of the most unique set ups: Extended moves & Reversal plays
Time for a 🧵 to learn the above from @iManasArora
What qualifies for an extended move?
30-40% move in just 5-6 days is one example of extended move
How Manas used this info to book
The stock exploded & went up as much as 63% from my price.
— Manas Arora (@iManasArora) June 22, 2020
Closed my position entirely today!#BroTip pic.twitter.com/CRbQh3kvMM
Post that the plight of the
What an extended (away from averages) move looks like!!
— Manas Arora (@iManasArora) June 24, 2020
If you don't learn to sell into strength, be ready to give away the majority of your gains.#GLENMARK pic.twitter.com/5DsRTUaGO2
Example 2: Booking profits when the stock is extended from 10WMA
10WMA =
#HIKAL
— Manas Arora (@iManasArora) July 2, 2021
Closed remaining at 560
Reason: It is 40+% from 10wma. Super extended
Total revenue: 11R * 0.25 (size) = 2.75% on portfolio
Trade closed pic.twitter.com/YDDvhz8swT
Another hack to identify extended move in a stock:
Too many green days!
Read
When you see 15 green weeks in a row, that's the end of the move. *Extended*
— Manas Arora (@iManasArora) August 26, 2019
Simple price action analysis.#Seamecltd https://t.co/gR9xzgeb9K
Those who exited at 1500 needed money. They can always come back near 969. Those who exited at 230 also needed money. They can come back near 95.
Those who sold L @ 660 can always come back at 360. Those who sold S last week can be back @ 301
Sir, Log yahan.. 13 days patience nhi rakh sakte aur aap 2013 ki baat kar rahe ho. Even Aap Ready made portfolio banakar bhi de do to bhi wo 1 month me hi EXIT kar denge \U0001f602
— BhavinKhengarSuratGujarat (@IntradayWithBRK) September 19, 2021
Neuland 2700 se 1500 & Sequent 330 to 230 kya huwa.. 99% retailers/investors twitter par charcha n EXIT\U0001f602