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Free monthly learning resources and insights https://gilesknowledge.substack.com/ Here are the links to the machine learning resources mentioned: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/ https://opentechschool.github.io/python-data-intro/core/recap.html https://www.kaggle.com/learn/intro-to-machine-learning https://developers.google.com/machine-learning/crash-course/ https://www.tensorflow.org/tutorials https://machinelearningmastery.com/start-here/ https://www.youtube.com/playlist?list=PL8erL0pXF3JYm7VaTdKDaWc8Q3FuP8Sa7 https://mml-book.github.io/ https://www.probabilitycourse.com/chapter1/1_1_0_what_is_probability.php https://www.statisticsdonewrong.com/ https://github.com/ageron/handson-ml3 https://courses.cs.duke.edu/spring20/compsci527/papers/Domingos.pdf https://datascience.stackexchange.com/ https://stats.stackexchange.com/?tags=machine-learning https://pytorch.org/tutorials/ https://scikit-learn.org/stable/tutorial/index.html That's 16 in total! Learn Data Science 🎓 Data Quest - https://bit.ly/3yClqbZ Learn Python with Giles 🎓 Exploratory Data Analysis with Python and Pandas - https://bit.ly/2QXMpxJ 🎓 Complete Python Programmer Bootcamp - http://bit.ly/2OwUA09 📚 My favourite python books for beginners (affiliate links) 📗 Python Crash Course 2nd Edition https://amzn.to/33tATAE 📘 Automate the Boring Stuff with Python https://amzn.to/3qM1DFl 📙 Python Basics - A Practical Introduction to Python 3 https://amzn.to/3fHRMdb 📕 Python Programming An Introduction to Computer Science https://amzn.to/33VeQCr 📗 Invent Your Own Computer Games with Python https://amzn.to/3FM3H4b 🆓 Free Python Resource https://python-programming.quantecon.org/intro.html (This is a great introduction to python) ⚙ My Gear 💡 BenQ Screen Bar Desk Light - https://amzn.to/3tH6ysL 🎧 Sony Noise Cancelling Headphones - https://amzn.to/3tLl82G 📱 Social Media https://www.instagram.com/gilesmcmullen/ https://twitter.com/GilesMcMullen 👌 SUBSCRIBE to ME!👌 https://www.youtube.com/channel/UC68KSmHePPePCjW4v57VPQg?sub_confirmation=1 #learnmachinelearning #machinelearning #learnpython

Let’s Understand The Model Architecture

In the rapidly evolving landscape of artificial intelligence, Generative AI, especially Language Model Machines (LLMs) have emerged as the…

In the age of burgeoning data complexity and high-dimensional information, traditional databases...

A Roadmap to Becoming an AI Engineer — From Zero to AI Engineer

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Explore this post and more from the learnmachinelearning community

Getting into machine learning is quite the adventure. And as any adventurer knows, sometimes it can be helpful to have a compass to figure out if you're heading in the right direction. Although the title of this video says machine learning roadmap, you should treat it as a compass. Explore it, follow your curiosity, learn something and use what you learn to create your next steps. Links: Interactive Machine Learning Roadmap - https://dbourke.link/mlmap Machine Learning Roadmap Resources - https://github.com/mrdbourke/machine-learning-roadmap Learn ML (beginner-friendly courses I teach) - https://www.mrdbourke.com/ml-courses/ ML courses/books I recommend - https://www.mrdbourke.com/ml-resources/ Read my novel Charlie Walks - https://www.charliewalks.com Timestamps: 0:00 - Hello & logistics 0:57 - PART 0: INTRO 1:42 - Brief overview of topics 3:05 - What is machine learning? 4:37 - Machine learning vs. traditional programming 7:41 - Why use machine learning? 8:44 - The number 1 rule of machine learning 10:45 - What is machine learning good for? 14:27 - How Tesla uses machine learning 17:57 - What we're going to cover in this video 20:52 - PART 1: Machine Learning Problems 22:27 - Categories of learning 26:17 - Machine learning problem domains 29:04 - Classification 33:57 - Regression 39:35 - PART 2: Machine Learning Process 41:57 - 6 major steps in a machine learning project 43:57 - Data collection 49:15 - Data preparation 1:04:00 - Training a model 1:23:33 - Analysis/evaluation 1:26:40 - Serving a model 1:29:09 - Retraining a model 1:30:07 - An example machine learning project 1:33:15 - PART 3: Machine Learning Tools 1:34:20 - Machine learning tools overview 1:38:36 - Machine learning toolbox (experiment tracking) 1:39:54 - Pretrained models for transfer learning 1:41:49 - Data and model tracking 1:43:35 - Cloud compute services 1:47:07 - Deep learning hardware (build your own deep learning PC) 1:47:53 - AutoML (automatic machine learning) 1:51:47 - Explainability (explaining the outputs of your machine learning model) 1:53:38 - Machine learning lifecycle (tools for end-to-end projects) 1:59:24 - PART 4: Machine Learning Mathematics 1:59:37 - The main branches of mathematics used in machine learning 2:03:16 - How I learn the math for machine learning 2:06:37 - PART 5: Machine Learning Resources 2:07:17 - A warning 2:08:42 - Where to start learning machine learning 2:14:51 - Made with ML (one of my favourite new websites for ML) 2:16:07 - Wokera ai (test your AI skills) 2:17:17 - A beginner-friendly path to start machine learning 2:19:02 - An advanced path for learning machine learning (after the beginner path) 2:21:43 - Where to learn the mathematics for machine learning 2:22:23 - Books for machine learning 2:24:27 - Where to learn cloud services 2:24:47 - Helpful rules and tidbits of machine learning 2:26:05 - How and why you should create your own blog 2:28:29 - Example machine learning curriculums 2:30:19 - Useful machine learning websites to visit 2:30:59 - Open-source datasets 2:31:26 - How to learn how to learn 2:32:57 - PART 6: Summary & Next Steps Connect elsewhere: Get email updates on my work - https://dbourke.link/newsletter Support on Patreon - https://bit.ly/mrdbourkepatreon Web - https://dbourke.link/web Quora - https://dbourke.link/quora Medium - https://dbourke.link/medium Twitter - https://dbourke.link/twitter LinkedIn - https://dbourke.link/linkedin #machinelearning #datascience

Follow these roadmaps to become an Artificial Intelligence expert.

Normcore LLM Reads. GitHub Gist: instantly share code, notes, and snippets.

1. How to build AI tools like ChatGPT?2. How to learn Machine Learning?3. How to learn Deep Learning?I will answer all these questions in this video.► All li...

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What's the big deal, intuition on query-key-value vectors, multiple heads, multiple layers, and more.

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Here’s everything you need to go from beginner to expert in AI:

Banana provides inference hosting on serverless GPUs for machine learning models. Deploy on Banana in three easy steps and a single line of code.

Proving you're a human on a web flooded with generative AI content

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Sheet1 Post Title,Date,URL,Title,Summary,Tags,,,,,,,,,,,,,, Saucy AI and Models,2022-10-10,a href="https://arxiv.org/pdf/2210.03142.pdf"https://arxiv.org/pdf/2210.03142.pdf/a Saucy AI and Models,2022-10-10,a href="https://twitter.com/hojonathanho/status/1577712621037445121"https://twitter....

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