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Have you ever been fascinated by the capabilities of large language models like GPT-4 but wondered how they are actually work? If you want to uncover the mysteries behind these powerful models, our latest video course on the freeCodeCamp.org YouTube channel is perfect for you. In this comprehensive course, you

We all have our own favorite tech stack, but is there a tech stack that can rule them all?Well, according to stack overflow, there is! In this video, we look...

Embeddings are a really neat trick that often come wrapped in a pile of intimidating jargon. If you can make it through that jargon, they unlock powerful and exciting techniques …

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As a prompt engineer, you will be responsible for crafting prompts that allow AI models to generate accurate and varied outputs.

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Vector Databases simply explained. Learn what vector databases and vector embeddings are and how they work. Then I'll go over some use cases for it and I briefly show you different options you can use. Resources: - Gentle introduction: https://frankzliu.com/blog/a-gentle-introduction-to-vector-databases - What is a vector database: https://www.pinecone.io/learn/vector-database/ Get your Free Token for AssemblyAI👇 https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_pat_75 00:00 - Intro 00:44 - Why do we need vector databases 01:29 - Vector embeddings and indexes 02:58 - Use cases 03:45 - Different vector databases Vector Database Options: - Pinecone - Weaviate - Chroma - Redis - Qdrant - Milvus - Vespa ▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬▬ 🖥️ Website: https://www.assemblyai.com 🐦 Twitter: https://twitter.com/AssemblyAI 🦾 Discord: https://discord.gg/Cd8MyVJAXd ▶️ Subscribe: https://www.youtube.com/c/AssemblyAI?sub_confirmation=1 🔥 We're hiring! Check our open roles: https://www.assemblyai.com/careers ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #MachineLearning #DeepLearning

Embeddings and Vectors are a great way of storing and retrieving information for use with AI services. OpenAI provides a great embedding API to do this. Postman lets you make these with easy at https://www.postman.com/ (today's sponsor) In this video we will explore how to create a Vector Database by creating embeddings using the OpenAI API and then storing them in SingleStore. The first part of the video will cover how to create an embedding using just API requests with Postman. Then we will jump into Single Store and store these in a new database made specifically for vectors like this. 00:00 - Introduction 00:10 - What are Embeddings and Vectors 02:14 - Setup OpenAI Embeddings 03:11 - Setup Postman API Requests to create Embeddings 03:55 - Create Embedding 03:55 - Create Embedding 06:55 - Create PDF or Document Embedding 07:43 - Vector Database - Setup with SingleStore 08:20 - Vector Database - Create Database 09:32 - Vector Database - Create Table 10:41 - Vector Database - Insert Embedding Row 13:25 - Vector Database - Search Embeddings 15:18 - Embedding function with JavaScript and NodeJS 18:08 - OpenAI and GPT Digital Book 18:29 - Conclusion Postman: (today's Sponsor) for API Requests https://www.postman.com/ OpenAI Embedding Documentation: https://platform.openai.com/docs/api-reference/embeddings SingleStore Vector Database https://www.singlestore.com/cloud-trial/?utm_campaign=adrian-twarog&utm_medium=video&utm_source=youtube ⭐ Teach Me OpenAI & GPT - Digital Book ⭐ https://enhanceui.gumroad.com/l/teach-me-openai Learn Design for Developers! A book I've created to help you improve the look of your apps and websites. 📘 Enhance UI: https://www.enhanceui.com/ Feel free to follow me on: 🐦 Twitter: https://twitter.com/intent/follow?screen_name=adrian_twarog 💬 Discord: https://discord.gg/6gmmFvxkD7 💸 Patreon: https://www.patreon.com/adriantwarog Software & Discounts: 🚾 Webflow: https://webflow.grsm.io/adrian 🌿 Envato: https://1.envato.market/yRZjz2 🌿 Envato Elements: https://1.envato.market/LP0OJZ 🔴 Elementor: https://elementor.com/adrian/?ref=23140 ✖ Editor X: https://www.editorx.com/adrian-twarog Computer Gear: ⬛ Monitor: https://amzn.to/3f9DOQI ⌨ Keyboard: https://amzn.to/3eA5UFD 🐁 Mouse: https://amzn.to/3xVJO8l 🎤 Mic: https://amzn.to/3hgCfms 📱 Tablet: https://amzn.to/3ewt7sa 💡 Lighting: https://amzn.to/3vOZeZY 💡 Key Lighting: https://amzn.to/3f6qP2f Camera Equipment: 📷 Camera: https://amzn.to/3uCv4J9 📸 Primary Lens: https://amzn.to/3vT6wMm 📸 Secondary Lens: https://amzn.to/3tyqWIX 🎥 Secondary Camera: https://amzn.to/3o2zCGi 🎙 Camera Mic: https://amzn.to/33tCz9l 🎞 USB to HDMI: https://amzn.to/33yW9RE

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Find out everything you need to know about learning AI in 2023, from tips to get you started, helpful resources, and insights from industry experts.

1/ Starting my road to learning about AI. I’ve done some courses here and there but I am planning a more consistent effort over the next few years. Mostly documenting my path for others and for fun. Often people suggest things I didn’t know which can be helpful.

Learn Machine Learning in a way that is accessible to absolute beginners. You will learn the basics of Machine Learning and how to use TensorFlow to implement many different concepts. ✏️ Kylie Ying developed this course. Check out her channel: https://www.youtube.com/c/YCubed ⭐️ Code and Resources ⭐️ 🔗 Supervised learning (classification/MAGIC): https://colab.research.google.com/drive/16w3TDn_tAku17mum98EWTmjaLHAJcsk0?usp=sharing 🔗 Supervised learning (regression/bikes): https://colab.research.google.com/drive/1m3oQ9b0oYOT-DXEy0JCdgWPLGllHMb4V?usp=sharing 🔗 Unsupervised learning (seeds): https://colab.research.google.com/drive/1zw_6ZnFPCCh6mWDAd_VBMZB4VkC3ys2q?usp=sharing 🔗 Dataets (add a note that for the bikes dataset, they may have to open the downloaded csv file and remove special characters) 🔗 MAGIC dataset: https://archive.ics.uci.edu/ml/datasets/MAGIC+Gamma+Telescope 🔗 Bikes dataset: https://archive.ics.uci.edu/ml/datasets/Seoul+Bike+Sharing+Demand 🔗 Seeds/wheat dataset: https://archive.ics.uci.edu/ml/datasets/seeds 🏗 Google provided a grant to make this course possible. ⭐️ Contents ⭐️ ⌨️ (0:00:00) Intro ⌨️ (0:00:58) Data/Colab Intro ⌨️ (0:08:45) Intro to Machine Learning ⌨️ (0:12:26) Features ⌨️ (0:17:23) Classification/Regression ⌨️ (0:19:57) Training Model ⌨️ (0:30:57) Preparing Data ⌨️ (0:44:43) K-Nearest Neighbors ⌨️ (0:52:42) KNN Implementation ⌨️ (1:08:43) Naive Bayes ⌨️ (1:17:30) Naive Bayes Implementation ⌨️ (1:19:22) Logistic Regression ⌨️ (1:27:56) Log Regression Implementation ⌨️ (1:29:13) Support Vector Machine ⌨️ (1:37:54) SVM Implementation ⌨️ (1:39:44) Neural Networks ⌨️ (1:47:57) Tensorflow ⌨️ (1:49:50) Classification NN using Tensorflow ⌨️ (2:10:12) Linear Regression ⌨️ (2:34:54) Lin Regression Implementation ⌨️ (2:57:44) Lin Regression using a Neuron ⌨️ (3:00:15) Regression NN using Tensorflow ⌨️ (3:13:13) K-Means Clustering ⌨️ (3:23:46) Principal Component Analysis ⌨️ (3:33:54) K-Means and PCA Implementations 🎉 Thanks to our Champion and Sponsor supporters: 👾 Raymond Odero 👾 Agustín Kussrow 👾 aldo ferretti 👾 Otis Morgan 👾 DeezMaster -- Learn to code for free and get a developer job: https://www.freecodecamp.org Read hundreds of articles on programming: https://freecodecamp.org/news

In this video, I give you my step by step process on how I would learn Machine Learning if I could start over again, and provide you with all recommended resources. All courses: https://github.com/AssemblyAI-Examples/ML-Study-Guide Get your Free Token for AssemblyAI Speech-To-Text API 👇 https://www.assemblyai.com/?utm_source=youtube&utm_medium=referral&utm_campaign=yt_pat_60 ▬▬▬▬▬▬▬▬▬▬▬▬ CONNECT ▬▬▬▬▬▬▬▬▬▬▬▬ 🖥️ Website: https://www.assemblyai.com 🐦 Twitter: https://twitter.com/AssemblyAI 🦾 Discord: https://discord.gg/Cd8MyVJAXd ▶️ Subscribe: https://www.youtube.com/c/AssemblyAI?sub_confirmation=1 🔥 We're hiring! Check our open roles: https://www.assemblyai.com/careers ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #MachineLearning #DeepLearning 0:00 Introduction 1:01 MATH 1:58 PYTHON PYTHON 2:37 ML TECH STACK ML TECH STACK 3:35 ML COURSES ML COURSES 4:44 HANDS-ON & DATA PREPARATION 5:17 PRACTICE & PRACTICE & BUILD PORTFOLIO 6:16 SPECIALIZE & CREATE BLOG

1. Learn broadly. 2. Learn deeply. 3. Don't be afraid to re-learn

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