A comprehensive guide into using NLP for Machine Learning

In this LangChain Crash Course you will learn how to build applications powered by large language models.

Learn how to use Microsoft JARVIS aka HuggingGPT for free right now. You can achieve multiple tasks with a single query using JARVIS.

JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf - microsoft/JARVIS: JARVIS, a system to connect LLMs with ML community. Paper: https://arxiv.org/pdf/...

An exploration into customizing LLMs for personal use

Prepare your M1, M1 Pro, M1 Max, M1 Ultra or M2 Mac for data science and machine learning with accelerated PyTorch for Mac.

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125 -...

archived 31 Mar 2023 11:16:52 UTC

Advanced playground tools for GPT-3

Supabase hired me to build ClippyGPT - their next generation doc search. We can ask our old friend Clippy anything you want about Supabase, and it will answer it using natural language. Powered by OpenAI + prompt engineering. In this video I will be showing you exactly how I did this, and how you can do the same in your projects. We'll be covering: - Prompt engineering and best practices - Working with a custom knowledge base via context injection + OpenAI embeddings - How to store embeddings in Postgres using pgvector Supabase blog post: https://supabase.com/blog/chatgpt-supabase-docs pgvector extension: https://github.com/pgvector/pgvector Generate embeddings implementation: https://github.com/supabase/supabase/blob/54d39d4958575e5b58aa1d5d2a02db863ab4673c/apps/docs/scripts/generate-embeddings.ts Clippy edge function implementation: https://github.com/supabase/supabase/blob/54d39d4958575e5b58aa1d5d2a02db863ab4673c/supabase/functions/clippy-search/index.ts Clippy frontend implementation: https://github.com/supabase/supabase/blob/54d39d4958575e5b58aa1d5d2a02db863ab4673c/packages/ui/src/components/Command/AiCommand.tsx Prompt engineering: https://prmpts.ai/blog/what-is-prompt-engineering 00:00 Why? 01:40 Let's get started 03:15 Custom knowledge base 04:49 Context injection 06:13 Pre-process MDX files 13:40 Embeddings 15:40 Storing in Postgres + pgvector 22:21 API endpoint (edge function) 23:44 Calculating similarity in pgvector 27:55 Prompt engineering 33:15 Prompt best practices 38:37 Demo time! 41:32 Thanks for watching!

Get instant answers, explanations, and examples for all of your technical questions.

In the journal Nature today, my colleagues and I published an article on the future directions of generative A.I. (aka Large Language or Foundation models) for the practice of medicine. These new AI models have generated a multitude of new and exciting opportunities in healthcare that we didn’t have before, along with many challenges and liabilities. I’ll briefly explain how we got here and what’s in store.

The historians of tomorrow are using computer science to analyze the past.

archived 10 Apr 2023 23:28:28 UTC

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Fear, FOMO, and the scientific exodus driven by ChatGPT

Cataclysm - Code generation library for the end game - Mattie/cataclysm: Cataclysm - Code generation library for the end game

CogSci 131 (Computational Modeling of Cognition) is one of my favorite classes at Berkeley when I took it with Prof. Tom Griffiths in 2016. Now I’m teaching it in my last semester. Before getting to the fun parts (e.g., implementing recurrent nets and classic RL algorithms like SARSA using vanilla NumPy), one needs to set up the right Python environment. I hope this tutorial can save students some headaches. Option #1: Conda Virtual Environment To avoid nightmares down the line👇, use virtual environments for your local stuff.

ChatGPT falsely claimed a mayor went to prison.

Accelerate the training of machine learning models with TensorFlow right on your Mac.

The hot startup is on the lookout for new executive talent to help bring in revenue, allowing CEO Emad Mostaque to focus on product development.

Here is How to make Harry Potter by Balenciaga Video: The actual video - https://www.youtube.com/watch?v=_N8RX3lIQDU Lets start: 🔹 Generate the image prompts with ChatGPT ChatGPT - https://chat.openai.com/chat ChatGPT prompts: 1. "Give me the 10 most popular Harry Potter characters, just the names." 2. "Now, act as a Balenciaga fashion designer with 20 years of experience. I want you to dress each of these 10 characters in a unique Balenciaga piece for a runway show. Just write the name of the character and the piece. Remember, it's a 1990 fashion show." 3. "Ok, now this is a prompt that I use to generate images from another AI image generation tool called Midjourney: '1990 screengrab of female model Hermione Granger wearing a grotesque black Balenciaga dress, fashion movie scene, Balenciaga commercial --ar 3:2 --v 5'. Just say 'Y' if you understand." 4. "I want you to rewrite the prompt but for every character, with the clothes you chose for them. Remember to write the prompt exactly as I pasted it, with the same format and parameters. Only change the gender of the model, the name of the character, and the description of the clothing. Do you understand? Please ask if you need more information." If you are very new to ChatGPT this 2 min video will help you get started. https://www.youtube.com/watch?v=AXn2XVLf7d0 🔹 Generate the images with MidJourney MidJourney (click join the beta) - https://www.midjourney.com/ If you are new to MidJourney this 5min tutorial is a great start. https://www.youtube.com/watch?v=90tXPbyRGS8 🔹 Upscale your images if they have poor resolution with Upscale.media Upscale.media - https://www.upscale.media/ 🔹 Generate the voiceovers with Elevenlabs. Elevenlabs - https://beta.elevenlabs.io/ If you are lost in the cloning part watch this 1min video. https://www.youtube.com/watch?v=3AtAiGtPi4s Youtube to MP3 converter - https://en.onlymp3.to/164/ MP3 cutter - https://mp3cut.net/ 🔹 Generate the AI animation with D-ID D-ID - https://www.d-id.com/ 🔹 Music track for the video - Thip Trong - Lightvessel https://www.youtube.com/watch?v=memDWTAvcXs Get the copyright for it with epidemicsound if you gonna use it for monitization on youtube. https://share.epidemicsound.com/fez7yf/?playlist=fguxfkbxipdhm3sh8hyu9ogtlf5vnezo Altenative copyright free song : (follow artist's terms&con) Dan Henig | Danger Snow https://www.youtube.com/watch?v=X4KYTFEJuFI&t=0s 🔹 Edit with capcut https://www.capcut.com/ In this step-by-step tutorial, learn how to create AI animated Harry Potter characters in the meme Balenciaga style. I will walk you through the entire process, from generating images using AI tools like ChatGPT and text-to-image tools like Midjourney, to creating immersive voiceovers with ElevenLabs, and finally, animating your characters with D-ID's text-to-video AI technology. And I also show you how to put all togother at the end. ‐------------------ - BACKGROUND MUSIC OF THIS VIDEO https://share.epidemicsound.com/fez7yf/?playlist=au0ut0ba17wivw3ipbbg1f9abaq4cba5 - VOICEOVER OF THIS VIDEO Synthesia - https://bit.ly/3yKHmDa ------------------- 🤖 OTHER AI TOOLS that I HAVE REVIEWED before* Synthesia - https://bit.ly/3yKHmDa HeyGen (Movio)- https://bit.ly/412eNx0 Colossyan Studio: https://bit.ly/3M6kKoC Elai - https://bit.ly/400pJvb D-ID - https://bit.ly/D-IDPromptJungle DEEPBRAIN - https://bit.ly/HumanAIPromptJungle My Other AI Animated Avatars videos: How To Create a Talking AI Avatar for FREE (better than synthesia) https://www.youtube.com/watch?v=kYueHEcqdmM Top 5 AI Generated Talking Avatar Tools (D-ID Alternatives) https://www.youtube.com/watch?v=U0HNdsxC8YU Create Multiple Talking Avatars in one Scene | AI Animated Avatars https://www.youtube.com/watch?v=hLOrHNK9-Hg Text to Speech Your Own Voice - ElevenLabs Cloning https://www.youtube.com/watch?v=3AtAiGtPi4s If my work speaks to you, hit the share button and spread the love on your socials. And if you're feeling extra kind, a coffee from you would be the cherry on top of my creative sundae! 🎶🌞☕️ https://linktr.ee/promptjungle *The AI links above are PromptJungle's affiliate links. If you make a purchase with my link there is no additional cost to you and in return PromptJungle makes a small commission. #tutorial #ai #harrypotter #balenciaga

You can install PyTorch for GPU support with a Mac M1/M2 using CONDA. It is very important that you install an ARM version of Python. In this video I walk you through all the steps necessary to prepare an Apple Metal Mac for my deep learning course in PyTorch. 0:27 Overview 1:00 Install Miniconda 1:49 Uninstall Anaconda (optional) 3:33 Install Miniconda 5:03 Install Jupyter 5:24 Install PyTorch 7:07 Create Jupyter Kernel Code for This Video: https://github.com/jeffheaton/t81_558_deep_learning/blob/pytorch/install/pytorch-install-aug-2022.ipynb ~~~~~~~~~~~~~~~ COURSE MATERIAL ~~~~~~~~~~~~~~~ 📖 Textbook - coming soon 😸🐙 GitHub - https://github.com/jeffheaton/t81_558_deep_learning/tree/pytorch ▶️ Play List - https://www.youtube.com/playlist?list=PLjy4p-07OYzuy_lHcRW8lPTLPTTOmUpmi 🏫 WUSTL Course Site - https://sites.wustl.edu/jeffheaton/t81-558/ ~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~ 🖥️ Website: https://www.heatonresearch.com/ 🐦 Twitter - https://twitter.com/jeffheaton 😸🐙 GitHub - https://github.com/jeffheaton 📸 Instagram - https://www.instagram.com/jeffheatondotcom/ 🦾 Discord: https://discord.gg/3bjthYv ▶️ Subscribe: https://www.youtube.com/c/heatonresearch?sub_confirmation=1 ~~~~~~~~~~~~~~ SUPPORT ME 🙏~~~~~~~~~~~~~~ 🅿 Patreon - https://www.patreon.com/jeffheaton 🙏 Other Ways to Support (some free) - https://www.heatonresearch.com/support.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #Python #Tensorflow #Keras

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks - GitHub - jeffheaton/t81_558_deep_learning: Washington University (in St. Louis) Course T81-558: Applicati...

How I run Anaconda and Miniforge side-by-side on my Mac M1 with TensorFlow and Keras.Install Locations* https://developer.apple.com/metal/tensorflow-plugin/*...

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks - t81_558_deep_learning/tensorflow-install-mac-metal-jan-2023.ipynb at master · jeffheaton/t81_558_deep_lea...

Many NLP applications require manual data annotations for a variety of tasks, notably to train classifiers or evaluate the performance of unsupervised models. Depending on the size and degree of complexity, the tasks may be conducted by crowd-workers on platforms such as MTurk as well as trained annotators, such as research assistants. Using a sample of 2,382 tweets, we demonstrate that ChatGPT outperforms crowd-workers for several annotation tasks, including relevance, stance, topics, and frames detection. Specifically, the zero-shot accuracy of ChatGPT exceeds that of crowd-workers for four out of five tasks, while ChatGPT's intercoder agreement exceeds that of both crowd-workers and trained annotators for all tasks. Moreover, the per-annotation cost of ChatGPT is less than $0.003 -- about twenty times cheaper than MTurk. These results show the potential of large language models to drastically increase the efficiency of text classification.