Python | Machine Learning | Coding | R
62.1K subscribers
1.12K photos
67 videos
140 files
770 links
List of our channels:
https://t.me/addlist/8_rRW2scgfRhOTc0

Discover powerful insights with Python, Machine Learning, Coding, and R—your essential toolkit for data-driven solutions, smart alg

Help and ads: @hussein_sheikho

https://telega.io/?r=nikapsOH
Download Telegram
⭐️ Large list of resources for Data Science practice

This is a selection of Python libraries, links to tutorials, links to code examples for solving DS problems.

🖥 GitHub: https://github.com/r0f1/datascience

〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️〰️
😘 More likes 💦 more posts 🙈
✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
Google, Harvard, and even OpenAI are offering FREE Generative AI courses (no payment required) 🎓

Here are 8 FREE courses to master AI in 2024:

1. Google AI Courses
5 courses covering generative AI from the ground up
https://www.cloudskillsboost.google/paths/118

2. Microsoft AI Course
Basics of AI, neural networks, and deep learning
https://microsoft.github.io/AI-For-Beginners/

3. Introduction to AI with Python (Harvard)
7-week course exploring AI concepts and algorithms
https://www.edx.org/learn/artificial-intelligence/harvard-university-cs50-s-introduction-to-artificial-intelligence-with-python

4. Prompt Engineering for ChatGPT (Vanderbilt)
6 modules on writing effective prompts for ChatGPT
https://www.coursera.org/learn/prompt-engineering

5. ChatGPT Prompt Engineering for Devs (OpenAI & DeepLearning)
Best practices and hands-on prompting experience
https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/

6. LLMOps (Google Cloud & DeepLearning)
Learn the LLMOps pipeline and deploy custom LLMs
https://www.deeplearning.ai/short-courses/llmops/

7. Big Data, AI, and Ethics (UC Davis)
4 modules on big data, IBM's Watson, and AI limitations
https://www.coursera.org/learn/big-data-ai-ethics

8. AI Applications and Prompt Engineering (edX)
Introductory course on prompt engineering and AI applications
https://www.edx.org/learn/computer-programming/edx-ai-applications-and-prompt-engineering

👉 To take Coursera courses for free, click 'Enroll for free' and 'Audit the course'.

〰️〰️〰️〰️〰️〰️〰️〰️〰️
😘 More likes 💦 more posts 🙈
✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
🖥 deepface - Python library for facial recognition and more

- pip install deepface

deepface is a lightweight Python library that allows you to find faces and analyze various attributes from photographs: age, gender, emotions.
It incorporates the best of the VGG-Face, FaceNet, OpenFace, DeepFace, DeepID, ArcFace, Dlib, SFace and GhostFaceNet models.

This is how you can compare the similarity of 2 faces, the result is in the image:
from deepface import DeepFace
result = DeepFace.verify(img1_path = "img1.jpg", img2_path = "img2.jpg")


🖥 GitHub
〰️〰️〰️〰️〰️〰️〰️〰️〰️
😘 More likes 💦 more posts 🙈
✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
🖥 SQL generator

Sqlcode 8b based on Llama-3 has been released!

This is probably the best <10B model currently available for converting text to SQL .

Works better than gpt-4-turbo and claude opus for generating SQL queries.

⭐️ Github: https://github.com/defog-ai/sql-eval

✅️ Weights: https://huggingface.co/defog/llama-3-sqlcoder-8b/

🟢 Demo (optimized for postgres): https://defog.ai/sqlcoder-demo/

✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
📌 Featuretools for feature generation

- python -m pip install featuretools

Featuretools is a Python library for automated feature development, i.e. defining variables from the data set for training the ML model.
Featuretools excels at converting temporal and relational datasets into feature matrices for machine learning.

🖥 GitHub
🧑‍💻 Docks

✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM
🖥 Open tutorial with Python basics

Not only basic topics are covered here, but also more advanced ones - such as working with datetime , itertools , os and other modules/libraries

Great source of information to look through before your interview.

▶️ Textbook 👈

✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM
🌟 Step-by-step implementation of the Transformer architecture

This laptop describes in as much detail as possible each step of implementing a transformer from scratch, with the necessary theoretical minimum
For complete enlightenment, you can combine it with video 3b1b

▶️ Jupyter Notebook

✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM
🖥 Gensim - Python library for working with natural language

pip install gensim

Gensim can be used for document indexing and similarity searches in large texts.
Gensim will be especially relevant for specialists in natural language processing (NLP) and information retrieval.

🖥 GitHub

✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
🖥 Data structures in Python - cheat sheet

Keep a powerful cheat sheet on data structures in Python; Everything is explained here with examples, so it will be crystal clear
Concepts such as mutability, immutability are described, things like list comprehensions and much more are described.

📎 Crib

✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM
⚡️ Big ML cheat sheet

Here you will find the basic theory of Machine Learning and examples of the implementation of specific ML algorithms - in general, this is just the thing to brush up on your knowledge before the interview.

📎 Crib

✅️ http://t.me/codeprogrammer ✅️
Please open Telegram to view this post
VIEW IN TELEGRAM
Please open Telegram to view this post
VIEW IN TELEGRAM