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🔺 The best GitHub repositories for learning Python
Learn Python for Data Science in 2024

👨🏻‍💻 In the latest data science report 2024 , Python is still the top programming language for data science with 56.7% . Here I have put a list of the best Python repositories for data science , which will improve your coding skills and guide you on the path to data science mastery.💯

1️⃣ Learn Python 3 repo
🖥 A collection of Jupyter notebooks for learning Python.
🐱 GitHub repo link

2️⃣ The Algorithms repo
🖥 All algorithms implemented in Python for training.
🐱 GitHub repo link

3️⃣ Awesome Python repo
🖥 A list of great Python frameworks, libraries, software, and resources.
🐱 GitHub repo link

4️⃣ 100 Days of ML repo
🖥 Learning algorithms and building neural networks without any programming experience.
🐱 GitHub repo link

5️⃣ Cosmic Python book repo
🖥 A book on Python's functional architectural patterns for managing complexity.
🐱 GitHub repo link

6️⃣ A Byte of Python book repo
🖥 If you do not learn Python programming, start with this book.
🐱 GitHub repo link

7️⃣ Python Machine Learning book repo
🖥 Python Machine Learning book code repository.
🐱 GitHub repo link

8️⃣ Repo of interactive interview challenges
🖥 120+ interactive Python coding interview challenges.
🐱 GitHub repo link

9️⃣ Repo of coding problems
🖥 Solutions for various coding/algorithmic problems.
🐱 GitHub repo link

1️⃣ Python Basics repo
🖥 A list of 300 Python interview questions + answer sheet.
🐱 GitHub repo link

1️⃣ Python programming exercises repo
🖥 100+ challenging Python programming exercises.
🐱 GitHub repo link
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In 1989, Yann LeCun and his team trained a LeNet 1 CNN, which was able to detect handwriting.

They published a video showing how this model can read the numbers that were written manually on a piece of paper, and then the model gives the numbers electronically.

The Convolution Neural Network CNN algorithm is considered one of the algorithms that has influenced the world and we find it nowadays in many fields.

In general, everything that can be predicted from an image or video is a CNN.
Many researchers relied on this algorithm and derived many of the most famous models from it (ResNet, DenseNet, MobileNet, SqueezeNet, VGG)

There are many models that come under the name CNN
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🔥🪄 Awesome-LLM : a curated list of Large Language Model

A curated list of articles, models, api, code examples, courses, datasets dedicated to large language models.

This is a well- structured academic selection.

Github

Other highly specialized awesome repositories dedicated to LLM:
Awesome-LLM-hallucination
Awesome-hallucination-detection
Awesome ChatGPT Prompts
Awesome ChatGPT
Awesome Deliberative Prompting
Instruction-Tuning-Papers
LLM Reading List
Reasoning using Language Models
Chain-of-Thought Hub
Awesome GPT
Awesome GPT-3
Awesome LLM Human Preference Datasets
RWKV-howto
ModelEditingPapers
Awesome LLM Security
Awesome-Code-LLM
Awesome-LLM-Compression
Awesome-LLM-Systems
Awesome-LLM-Healthcare
Awesome-LLM-Inference
Awesome-LLM-3D
LLMDatahub
Language models for Russian language

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Acquired global fresh database Please send me a sample Scammer please don't waste your time @yuefu666
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🟢 Yaoliang Yu, a professor at the School of Computer Science at the University of Waterloo, Canada, has published several free data science courses. These courses include machine learning, data science optimization, linear algebra and deep learning.

The resources of each course include textbooks, assignments, articles and projects during the course.

🔖 Guide to free data science courses at the University of Waterloo:


➡️ CS794 Fall 2022
🖥 Optimization for Data Science

➡️ CS480 Fall 2022
🖥 Introduction to Machine Learning

➡️ CS794 Fall 2021
🖥 Game Theoretic Methods in ML

➡️ CS480 Fall 2019
🧠 Theory of Deep Learning

➡️ CS475 Spring 2018
🖥 Computational Linear Algebra

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India's Largest Free Webinar on LLMs especially focused on the recently released LLAMA-3 by Meta.

How do you use these models?
How can you create apps with them?

Join our free workshop on to learn how to use Llama 3 and create apps with it.

Register here: https://www.buildfastwithai.com/events/llama-3-deep-dive

You can connect with Founder;
https://www.linkedin.com/in/satvik-paramkusham/

This Event is especially designed for people interested in the field of AI, ML, GenAI & LLMs.
📌 PyTorch Sentiment Analysis - analysis of the emotional component of the text

This repository contains different implementations of text analysis in PyTorch:
🔄 using a “bag of words”
🟰 using a recurrent neural network (RNN)
via convolutional neural network (CNN)
🔍 with the help of fashionable transformers

🖥 GitHub


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⭐️ 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

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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'.

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🖥 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
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🖥 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://www.tgoop.com/codeprogrammer ✅️
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📌 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://www.tgoop.com/codeprogrammer ✅️
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🖥 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://www.tgoop.com/codeprogrammer ✅️
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2024/09/22 03:02:35
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