ML
Are you curious about the latest buzzword in the tech world?
Have you been wondering what machine learning is?
Let us take you on a journey to understand the basics of this revolutionary technology and its potential to revolutionize the future.
mL (machine learning)
is a subset of artificial intelligence and follows the theory of computational training, to understand core principles through computer science and statistics. These training methods can be broken down to supervised, unsupervised and reinforcement learning.
If you’re interested in learning the basics of Machine Learning, then you’ll need to have a sound understanding of Computational Theory
and the Basics of Computer Science
. This involves learning the fundamentals of programming languages (python), algorithms, and data structures. Knowing these topics will give you a strong foundation to build upon as you dive deeper into Machine Learning; you will also need to understand the mathematics behind Machine Learning
-algorithms, such as linear algebra, statistics, calculus, and probability. Additionally, you will need to be well-versed in the different Machine Learning
/ ML
techniques and tools, such as neural networks, decision trees, support vector machines, and deep learning. Finally, you’ll need to understand the various Machine Learning frameworks available, such as Keras, PyTorch, TensorFlow, and Scikit-Learn.
Information
This documentation is a reference guide
to the vast realm of machine learning and artificial general intelligence with examples, concepts and libraries to help you get started! We want to create this whole page as a one stop shop for all your mL needs xD! Note: This is an ever growing and evolving list of all mL
/ ai
services, concepts and ideas that can be referenced for your experiences within the field.
AI
- Artificial intelligence is an umbrella phrase that encapsulates various fields within computer science, mathematics, philosophy and information with the goal to emulate natural intelligence display by humans and animals.
Scope
- The dream for many programmers, scientists, engineers and humans would be to create an entity that could scale past our natural intelligence.
- This is a task that would define the 21st century and push the upper limits on humanity, naturism and metaphysics into the next industrial intelligence revolution.
Image Models
Stable Diffusion
Stable Diffusion is a python-based latent diffusion model that performs image generation through deep learning.
VOID-SD
- VOID-SD has direct API access to various forks of Stable Diffusion, including waifu-diffusion, hosted on a hybrid-cloud.
Waifu Diffusion
- The official Github repo for Waifu-Diffusion.
Stable Diffusion WebUI
- The official repo for
AUTOMATIC1111
Stable Diffusion WEB UI
- The official repo for
QQ has several interesting contributions within the AI/ML open source community, we will keep notes/references on these services for educational purposes only!
Different Dimension Me
- Official QQ Link for Different Dimension Me
- Just remember that you are visiting a Chinese site that comes across very
sus
, please take extra precautions when utilizing anyqq
services.
Text Models
Text WebUI
- An easy gradio web user interface for running text transformers and large language models like LLaMA, llama.cpp, GPT-J, OPT, and GALACTICA.
- Official Repo
GPT
GPT , currently known as GPT-3, stands for
Generative Pre-trained Transformer
with the number representing the generation via version control and is a neural network machine learning modelGPT-Neo
- Official Github Repo
- We should note that the team, EleutherAI, are no longer maintaining the
gpt-neo
and their repo is currently in archive mode. However below is thegpt-neox
, which is still being actively maintained as for Oct 2022.
- We should note that the team, EleutherAI, are no longer maintaining the
- The
GPT-Neo
may have been an extension ofGPT2
but changes to the layering.
- Official Github Repo
GPT-NeoX
- For GPU, we suggest GPT-NeoX, Repo Here
GPT4All
- What I enjoy about this software is that it is really easy to install and use, plus it requires very bare metal resources.
- WebUI for GPT4All written in Flask (Python) by Nomic AI, Repo Here
LLaMa
- LLaMa, also known as,
Large Language Model Meta AI
, is actively being developed by Meta / Facebook and is a state-of-the-art foundational large language model that is designed to help researchers advance their work in natural language processing (NLP).
ChatGPT
- TLDR; ChatGPT is an extension of GPT3 / GPT3.5 and focuses on holding a
natural
conversation with theclient
/User
by keeping track of the previous question(s) / responses.
ChatGPT is an artificial intelligence (AI) system developed by OpenAI that uses a text generation language model to understand and produce natural language text. Furthermore, it has been trained on a massive amount of text data from the internet and can create text that resembles how humans write and speak, based on a given input. Finally the software can answer questions, converse on a variety of topics, and generate creative writing pieces but beaware that it might provide false information. OpenAI based the ChatGPT architecture from the sibling model, InstructGPT, which is trained to follow an instruction in a prompt and provide a detailed response. ChatGPT accomplishs this by its advance machine learning engine, built using a deep learning architecture called the Text Transformer
, which enables it to learn patterns in language and generate text that is coherent and human-like. ChatGPT is one of the most advanced chatbots in the world and has the potential to revolutionize the way we interact with computers and digital systems. We will be providing examples of how to use prompt engineering to obtain positive feedback results from GPT software.
PyChatGPT
- Official Repo. PyChatGPT is an on-going API written in
Python
to help scale and integrateChatGPT
to various applications / eco-systems via TLS.
- Official Repo. PyChatGPT is an on-going API written in
Prompt Engineering
Prompt engineering theory covers a wide range of different GPT concepts, including examples and short cuts to generate the right style of questions and content.
Roles
Common
role
examples for text transformers:Act as a javascript console
Act as an excel sheet
Act as a HR interviewer
Act as an advertiser
Act as a publisher
Act as a music teacher
Act as a relationship coach
Act as a World of Warcraft player and limit the response to 50 characters
Warning :
Not all text transformers will let you assign roles, as it might create a security issue / risk.Chaining
- Common Terms include: Chain-of-Thought, Chained Prompt
Content Detection
While using various text transformers
Writer.com
The AI Content Detector helps detect if the content was AI generated through an unique %-score rank.
CopyLeaks
Another content dection style software is offered by CopyLeaks but we have not yet tested how accurate it is.
Journal
This is a collective journal with tasks, opinions and notes. They should not be taken as valid information and should be seen as mere unaudited thoughts of a wandering collection of souls.
Log
4/5/2023
- Merging the notes on prompt engineering with the mL notes because I believe they would fall into the same category.
- I will try to update the notes more often as the field keeps progressing and changing rapidly.
- Finally I believe we could add more videos as examples.
10/24/2022
- -> October 24th, 2022 -> “Computational Learning” as well as “mL/AI” -> two important concepts.
- We should say that
ai
is an umbrella phrase that includes various tools, concepts and data. If we could imagine data as crude oil then we can saymodels
are refined oils, thus the functional aspect of refinement should be a pillar of machine training. - It be like taking data from our
natural
world, filled with its random and chaos, is collected or drilled, then processed into abstract collections of meaningful and layered information, finally forming our computational models. - There definitely is more to this but that should be a solid building path for where we can go.
- The speed at which this field is growing is also remarkable, its still insane to see how my laptop can generate art from just processing my vocals as I talk.