Machine Learning

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Don't forget to try it; it's free and includes most AI models.

Machine Learning pinned a photo

🔥 More models. Lower cost. One API key.

Access GPT, Claude, Grok, Gemini, DeepSeek, Kimi, Qwen and more through one gateway.

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Access leading models at prices below official API list rates.

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Updated CS 8803 "Large Language Model" course at Georgia Tech for 2026.

The list of materials covers pre-training, Mixture of Experts (MoE), reasoning, reinforcement learning and self-play, agents, long context, scaling during inference, diffusion language models, safety, interpretability, and much more.

- https://cocoxu.github.io/CS8803-LLM-spring2026/

- https://docs.google.com/spreadsheets/d/1Oisf4imoNL3fs4UWGYAUlMCuYfCACMHCDb0iqEYU8wc/edit?usp=sharing

📚 "Natural Language Processing and Large Language Models" is a new open-access book from Springer, written by Chengqing Zong, Yang Zhao, and Yanjun Ma.

It's almost 400 pages long and provides an introduction to modern natural language processing and large language models.

Inside, you'll find information on: neural networks, distributed representations, language models, Transformers, BERT, GPT, tokenization, sentiment analysis, information extraction, text summarization, natural language understanding, machine translation, question answering, and RLHF.

In my opinion, this is a good reference guide for those who want to understand these topics without a very high barrier to entry. I would recommend it. ✨

https://link.springer.com/book/10.1007/978-981-92-0682-7

#NLP #LLM #ArtificialIntelligence #MachineLearning #DataScience #TechBooks

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A Collection of Machine Learning Libraries for Python 🤖

A large repository containing over 900 libraries and frameworks for machine learning. 📚

All projects are sorted by quality and popularity, which helps you quickly find the best tools for working with AI and ML. ⚙️

Repo: https://github.com/ml-tooling/best-of-ml-python?tab=readme-ov-file#vector-similarity-search-ann

#MachineLearning #Python #AI #DataScience #MLTools #Programming

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🔖 ML algorithms in visualizations

A useful repository that helps you understand how machine learning algorithms work – through interactive diagrams and step-by-step explanations.

You can run it in your browser or locally using Docker.

⛓ Link to GitHub
https://github.com/gavinkhung/machine-learning-visualized

CS189 self-study run: Convolutional Neural Networks 🧠📚

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🚀 21-Day CCNA & CCNP Sprint – Aug 17 to Sep 6
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#DS #Archive #DataScience #Tech #News #Update

🔔 Still Available!

400 Machine Learning Interview Questions with Answers 2026

Machine LearningnInterview Questions Practice Test | Freshers to Experienced | Detailed Explanations for Each Question…

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🤖 AI & Machine Learning

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"The Mathematics of Bitcoin" is a concise work that analyzes Bitcoin from a mathematical perspective. 📊

It utilizes probability theory, stochastic processes, martingales, combinatorics, and special functions to explore the mechanisms of the Bitcoin protocol. 🧮

In particular, the authors examine the probability of double-spending, the profitability of mining, block generation, miner strategies, and the resilience of the protocol. ⛏️

If you want to delve deeper, I also recommend "Bitcoin and Cryptocurrency Technologies" from Princeton University. This is a much broader introduction to cryptographic hash functions, digital signatures, consensus, Proof of Work, mining, transactions, anonymity, security, and the incentive system in cryptocurrencies. 🎓

Save both of these resources. They are excellent materials if you're interested in understanding the mathematics and technical mechanisms of Bitcoin. 💾

The Mathematics of Bitcoin:
https://arxiv.org/pdf/2003.00001

Bitcoin and Cryptocurrency Technologies:
https://d28rh4a8wq0iu5.cloudfront.net/bitcointech/readings/princeton_bitcoin_book.pdf

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🧿ANTHROPH\C Launches 13 Free AI Courses

Anthropic Academy has announced 13 free AI courses. The courses cover the following topics:

• Working with Claude
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• AI Agents
• Model Context Protocol (MCP)
• Claude Code
• Working with APIs
• Enterprise AI
• Google Cloud Vertex AI and Amazon Bedrock Integration


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2. AI Fluency: Framework & Foundations

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The courses are designed for a wide audience, from beginners to developers, educators, students, and business owners.