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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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"Dive into Deep Learning" 📘🤖 is an open-source book that forms the mathematical foundation for large language models. 🧠📐
"Dive into Deep Learning" 📘🤖 is an open-source book that forms the mathematical foundation for large language models. 🧠📐 It covers linear algebra, mathematical analysis, probability theory, optimization methods, backpropagation, attention mechanisms, and transformer architectures. 🧮📉🔄 The book progressively moves from classical neural networks and convolutional neural networks to modern transformers and practical techniques used in large language models. 🚀🔗🧠 It contains over 1,000 pages 📖 and provides clear explanations, practical examples, and exercises. ✅📝 Making it one of the most comprehensive free resources for understanding the mathematical structure of modern artificial intelligence systems and language models. 🌐🔍🤖 arxiv.org/pdf/2106.11342 🔗 #DeepLearning #AI #MachineLearning #NeuralNetworks #Transformers #OpenSource

Repost from Machine Learning
🚀 Master Binary Classification with Neural Networks! 🧠✨ Ever wondered how to build a neural network from scratch in Python
🚀 Master Binary Classification with Neural Networks! 🧠✨ Ever wondered how to build a neural network from scratch in Python using NumPy? 🐍📊 Binary classification is at the heart of many machine learning applications. 🎯🤖 Our super-detailed guide walks you through the entire process step by step. 📝📚 💡 Dive in and start building your own neural network today! 🏗🔥 https://tinztwinshub.com/data-science/a-beginners-guide-to-developing-an-artificial-neural-network-from-zero/ #MachineLearning #NeuralNetworks #Python #DataScience #AI #Tech

AI is moving fast. Accountability is not. That is why we built the open source core of Forkit Dev. Forkit Dev introduces Model Passports and Agent Passports so AI systems can be tracked, verified, and understood across their lifecycle. Open source repo: https://github.com/arpitasarker01/Forkit_Dev If you care about trustworthy AI, open source infrastructure, model lineage, or compliance ready deployment, check it out and share your thoughts.

Do you know that Python can shift sequences without slicing and creating new lists? 🤔 When you need to cyclically shift data, many use slicing:
data = data[-1:] + data[:-1]
But deque.rotate() does this at the level of the data structure and usually works more efficiently for cyclical operations. 🚀
q.rotate(1)
A negative value rotates the queue in the other direction. ⬅️
q.rotate(-2)
This is useful for ring buffers, task schedulers, cyclical queues, and round-robin algorithms. 🔄
workers.rotate(-1)
🔥 deque.rotate() allows you to implement cyclical data structures without manual index logic and without creating new lists. 💡 👉 Python Ready | #tip #Python #Programming #Deque #CodingTips #Tech #DevCommunity

Do you know that Python can shift sequences without slicing and creating new lists? When you need to cyclically shift data, many use slicing:
data = data[-1:] + data[:-1]
But `deque.rotate() does this at the level of the data structure and usually works more efficiently for cyclical operations. ``python q.rotate(1)
A negative value rotates the queue in the other direction.
python q.rotate(-2)
This is useful for ring buffers, task schedulers, cyclical queues, and round-robin algorithms.
python workers.rotate(-1) ` 🔥 `deque.rotate()` allows you to implement cyclical data structures without manual index logic and without creating new lists. #Python #deque #rotate #Programming #Coding #DevTips

Repost from Machine Learning
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Cheat sheet on the basics of Python: 🐍📚 basic syntax and language rules 📝 scalar types — basic data types (int, float, boo
Cheat sheet on the basics of Python: 🐍📚 basic syntax and language rules 📝 scalar types — basic data types (int, float, bool, str, NoneType) 🔢 datetime — working with date and time 📅⏰ data structures — Python data structures (list, tuple, dict, set) 🗄 list — mutable lists for storing data collections 📋 tuple — immutable sequences of values 🔒 dict (hash map) — storing data in a key-value format 🗝 set — unique elements without order 🔘 slicing — obtaining parts of sequences through indices and step ✂️ module/library — connecting modules and libraries 🔌 help functions — using help() and dir() to explore the Python API 🛠 #Python #Coding #DataScience #Programming #Tech #DevCommunity

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reader3 📚✨ When you want to connect an AI like Gemini to help you analyze books or content, copying text from a reader usual
reader3 📚✨ When you want to connect an AI like Gemini to help you analyze books or content, copying text from a reader usually becomes a hassle. 😩💻 Especially if you want to discuss a book by chapters. Highlighting text manually and copying it disrupts the flow and feels like a waste of time. ⏳🚫 Yesterday, Andrzej Karpati, a well-known AI expert, released a new project to the public: reader3, which solves this problem very neatly. 🎉🛠️ It's a lightweight EPUB reader that allows you to read a book together with AI. 🤖📖 Its interface is as minimalist as possible: only the necessary reading and navigation functions. 📉🧭 You can also manage your library through folders. 📁✨ The key feature is that it breaks an EPUB into chapters and displays the content one chapter at a time. 🔓📄 This makes it easy to copy the needed part of the book and pass it to a large model for analysis or discussion. 📋🔄 It significantly improves the reading experience when paired with AI. 🚀🧠 And it's very easy to get started - just run two commands via uv. ⚡🛠️ As a result, it's an excellent tool for those who love reading and want to use AI as a companion for text analysis. 📚🤝🤖 📁 Language: #Python 61.0% ⭐️ Stars: 1.5k ➡️ Link to GitHub https://github.com/karpathy/reader3 #AI #Python #Reader3 #Tech #BookLovers #Github https://t.me/CodeProgrammer

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