Shankar Nag

Struggle➜Survive ➜Rise ➜Dominate➜Rule

బలం విష్ణో: ప్రవర్ధతాం

[Shankar Nag @ShankarN]

#KingKohli 👑

[Shankar Nag @ShankarN]

@Manu_Sisti @Founder_Tribune Claude

[Manu Sisti @Manu_Sisti]

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[Shankar Nag @ShankarN]

@Value_Finance12 @destinyOT2 @itswpceo Is this true @grok

Can india hit US with latest ICBM

[Shankar Nag @ShankarN]

@grok please find ai engineering posts today

[Shankar Nag @ShankarN]

@grok find this tweet link

[Shankar Nag @ShankarN]

@grok @grok top ten visits to my profile

[Shankar Nag @ShankarN]

Hey,

@grok, who was the most famous person to visit my profile? It doesn't need to be a mutual, don't tag them, just say who it was

[Shankar Nag @ShankarN]

@grok @grok Are you saying elon musk visited my profile

[Shankar Nag @ShankarN]

@elonmusk @xai @AskPerplexity verify this statement and answer

[Shankar Nag @ShankarN]

Enni rojulu ila Desam mida padi fan wars chesthav ra @grok , aa @GeminiApp paapa ni line lo pettu asaley @ChatGPTapp full try chesthunadu @GeminiApp paapa kosam

[Shankar Nag @ShankarN]

Entra sangathulu @grok bammardi

[Shankar Nag @ShankarN]

@grok harihara veera mallu movie ela undi

[Shankar Nag @ShankarN]

Rey @grok em chesthunav

[Santiago @svpino]

Here are 50 algorithms every programmer should know:

Let's start with my top favorite 10. If nothing else, you should read about these algorithms and have a good idea of how they work:

1. Linear search to find an element in a list
2. Binary search to find an element on a sorted list
3. Bubble sort to sort a list
4. Merge sort will also sort lists
5. Quicksort to sort the list and do it fast
6. Dijkstra to find the shortest path in a graph
7. Breadth-first Search (BFS) for trees or graphs
8. Depth-first search (DFS) for trees or graphs
9. Huffman for doing data compression
10. Anything related to dynamic programming

Learning about algorithms is like getting tattoos: you never have enough. Here are another 5 algorithms that will help you go beyond the basics:

11. Kruskal for the finding minimum spanning tree
12. Floyd Warshall, shortest paths in a graph
13. Union Find to detect cycles in a graph
14. Bellman-Ford, shortest path in a graph
15. Lee for finding the shortest path in a maze

If you are serious about this topic, I recommend learning about algorithms' space and time complexity. People usually refer to this topic as "Big O" notation. You should build a good intuition about the performance of different algorithms and learn how to evaluate them.

Machine Learning will rule the next 50 years, so the next 10 algorithms you can't ignore are the following:

16. Linear Regression
17. Logistic Regression
18. Decision Trees
19. Bayes' theorem
20. k-Nearest Neighbors (kNN)
21. Every algorithm related to neural networks
22. K-means
23. Random forest
24. Gradient boosting algorithms
25. Any dimensionality reduction algorithm (PCA, for instance)

There are many more mind-blowing algorithms! I haven't found a better way to understand how computers work from a first-principles point of view than reading about different algorithms.

I only mentioned 25 algorithms here, so here is a book if you want to learn a bit more:

https://t.co/M4nd2p3Gbq

[Maxwell 🕊 @MindWisdomMoney]

RIP web developers

Imagine building a website in a matter of minutes using only AI.

Here's how easy it is :

(Thread)

[Akshay 🚀 @akshay_pachaar]

Kaggle offers top-notch courses in Data Science, and surprisingly, many of us haven't heard about them.

Some of the salient features:

- No pre-requisites
- Completion time: 3 to 5 hours
- Guided projects for hands-on learning
- Comprehensive coverage of all topics

Now, let's take a look at the topics covered in these courses.

1️⃣ Python

Two courses, one for absolutes beginners & other dedicated to Python for Data Science

2️⃣ Machine Learning

Learn the core ideas in ML & build your first ML model, focused on classical Machine Learning.

3️⃣ Data Analysis

This course covers the basics of data wrangling using pandas and data visualization. It also includes short hands-on challenges.

4️⃣ Feature Engineering

Better features make better models, the course teaches you to discover how to get the most out of your data.

5️⃣ SQL Intro & Advanced

Learn the basics of SQL to work with databases & the take your SQL skills to next level in the advanced course

6️⃣ Intro to Deep Learning

Use TensorFlow and Keras to build and train neural networks for structured data.

7️⃣ Computer Vision

Learn how to build convolutional neural networks using TensorFlow and Keras.

8️⃣ Time Series

This course teaches you how to apply machine learning for real-world forecasting. Topics covered include time series data manipulation, feature engineering, and model evaluation.

9️⃣ Intro to AI Ethics

With advancing artificial intelligence (AI), it's crucial to align its design with moral and ethical principles. This course offers practical tools for morally designing AI systems.

🔟 Intro to Game AI & Reinforcement Learning

Build your own video game bots, using classic and cutting-edge algorithms.

Find all these course here: https://t.co/AjNnCQSPRi

That's all, if you’re interested in:

- Python 🐍
- ML/MLOps 🛠
- CV/NLP 🗣
- LLMs 🧠

Find me → @akshay_pachaar ✔️
Newsletter → https://t.co/Nm43nqDnpG

Everyday, I share tutorials on above topics!

Cheers!🥂

[Akshay 🚀 @akshay_pachaar]

I started my career in Data Science back in 2016.

Here's a list of Tech YouTube Channels I've ardently followed:

1️⃣ Corey Schafer

Arguably the best python channel on YouTube 🔥

I have personally learned a lot from him ✅

Check this out 👇
https://t.co/hqCh6hHH4A

2️⃣ Andrej Karpathy

He's not only a pioneer but the best teacher in the world of AI.

Right now he's back at teaching & his latest series on makemore is something you don't want to miss.

Check this out👇
https://t.co/fGsl2D5px0

3️⃣ George Hotz Archive

The greatest hacker that I've known & CEO of comma. ai.

I can watch is programming live streams all day!!

A must follow for every programmer 👍

Check this out 👇
https://t.co/moXAJzAW8c

4️⃣ Lex Friedman

One of the top AI podcasts on YouTube.

Almost every big name in AI has been on this podcast.

Again one of my favourites. 🔥

Check this out 👇
https://t.co/gazNpEqPSy

5️⃣ Missing Semester

Content created by folks at MIT.

Teaches you how to master the command-line, use a powerful text editor, use fancy features of version control systems, and much more!

Check this out 👇
https://t.co/PjyBRizUPl

6️⃣ Computerphile

Videos all about computers and computer stuff.

Hands down, a must follow for every programmer!!

Check this out 👇
https://t.co/q3ju5wVPy1

7️⃣ StatQuest

BAM!!

Joshua Stammer's fun take on teaching Stats & Mathematics for ML to masses is an absolute gold mine 🥇

Check this out 👇
https://t.co/CwF28MLyvv

8️⃣ 3Blue1Brown

3Blue1Brown, by Grant Sanderson, is some combination of maths & entertainment.

Let alone a machine learning practitioner,
anyone who loves programming & maths must follow this channel.

Check this out 👇
https://t.co/p1M9ssSqmG

That's a wrap! 🙂

If you interested in:

- Python 🐍
- Data Science 📈
- Machine Learning 🤖
- Maths for ML 🧮
- MLOps 🛠
- CV/NLP 🗣
- LLMs 🧠

Find me → @akshay_pachaar ✔️
Everyday, I share tutorials on above topics!

Cheers! 🥂

[Ruchi Bhatia 👩‍💻 @ruchi798]

Just finished reading "Machine Learning with R". 📖Thanks to @PacktPublishing for this gem!

Brett Lantz simplifies ML, making it accessible for every R user. An excellent guide for data pre-processing, insight discovery, forecasting & creating compelling visualizations. 🎨

[Akshay 🚀 @akshay_pachaar]

Microsoft is offering FREE courses in following areas:

- AI
- IOT
- Data Science
- Machine Learning

A project-based pedagogy that allows you to learn while building! 🚀

Read More ...👇

[Alamin @iam_chonchol]

Google is offering free online courses with certification.

No Payment Needed.

Here are 12 FREE Google courses to become skilled in 2023 [ Thread ]: