The popular free LLM course has just been updated.
This is a step-by-step guide with useful resources and notebooks for both beginners and those who already have an ml-base.
The course is divided into 3 parts: 1️⃣LLM Fundamentals :The block provides fundamental knowledge of mathematics, Python and neural networks. 2️⃣LLM Scientist :This block focuses on the internal structure of LLMs and their creation using the latest technologies and frameworks. 3️⃣The LLM Engineer : Here you will learn how to write applications in a hands-on way and how to deploy them.
❤️Why Grab This Book? - Hands-On Learning: Transform raw data into insights using Python. Perfect for coders who want to dive into stats without drowning in formulas! - Real-World Case Studies: Analyze datasets from the National Institutes of Health and more. Learn by doing, not just theorizing! - Jupyter Notebooks Included: Every chapter comes with interactive notebooks—run code, tweak examples, and solve exercises seamlessly. Ideal for Colab or local setups! - Cutting-Edge Topics: Explore regression, time series analysis, survival analysis, and Bayesian methods. Level up your data science toolkit! - Free & Open Source: Licensed under Creative Commons (CC BY-NC-SA). Download the PDF, fork the GitHub repo, and start learning today!
💡Perfect For: - Python devs eager to add stats/data skills. - Data enthusiasts craving practical, code-driven analysis. - Educators seeking a modern, interactive stats resource.
☄️Why This Book? - Learn by Doing: Perfect for beginners and coders upgrading to Python 3! Hands-on examples, exercises, and projects. - Jupyter Notebook Edition: Entire book redesigned as interactive notebooks! Run code, visualize results, and experiment live. - Free & Open Source: Licensed under CC BY-NC-SA—download, share, and contribute! - From a Pro: Authored by Allen Downey, computer science professor and creator of the legendary *Think Series* (*Think Stats*, *Think Bayes*). - Clear & Engaging: Simplifies complex concepts with humor and real-world analogies.
📈New in the 3rd Edition: - Updated for modern Python 3 practices. - Fully integrated Jupyter notebooks for interactive learning. - Expanded exercises and case studies.
👩💻Perfect For: - New programmers starting with Python. - Educators teaching coding or data science. - Data enthusiasts who want to code smarter.
A brand-new, FREE course on LLM evaluations has just been launched in collaboration with Elvis Saravia! Dive into the world of AI model assessments and elevate your skills with cutting-edge insights.
📚What’s Included? - ⚖️ In-depth coverage of LLM-as-a-judge metrics, LLM unit testing, monitoring, and beyond - 🤖 Hands-on experience with real-world projects, such as building a YouTube search agent - 🎉 Access to open-source models via LiteLLM
Whether you're an AI enthusiast, developer, or researcher, this course is designed to empower you with practical knowledge and tools. Don’t miss out—enroll now to secure your spot! 👇 https://www.comet.com/site/llm-course/
If you're looking to understand and experiment with Transformer-XL using PyTorch, this resource provides a clean and complete implementation. Transformer-XL is a powerful model that extends the Transformer architecture with recurrence, enabling learning dependencies beyond fixed-length segments.
The implementation is ideal for researchers, students, and developers aiming to dive deeper into advanced language modeling techniques.
🚀 DataCamp has officially partnered with Polars**—a cutting-edge DataFrame library designed for speed and efficiency!
To mark this exciting collaboration, **DataCamp is offering free access to its brand-new course *“Introduction to Polars”* for the next 90 days. 🎉
This course is a great opportunity for learners and professionals alike to master data cleaning, transformation, and analysis with Polars' high-performance engine, lazy execution, and powerful groupby operations.
Unlock the full potential of data workflows and explore how Polars can supercharge large-scale data processing.
👨🏻💻 Real learning means implementing ideas and building prototypes. It's time to skip the repetitive training and get straight to real data science projects!
🔆 With the DataSimple.education website, you can access 40+ data science projects with Python completely free ! From data analysis and machine learning to deep learning and AI.
✏️ There are no beginner projects here; you work with real datasets. Each project is well thought out and guides you step by step. For example, you can build a stock forecasting model, analyze customer behavior, or even study the impact of major global events on your data.
