Machine Learning

Use Cases

Machine learning (ML) is a subset of artificial intelligence (AI). It is great for making predictions based on historical data. [1]

Use-cases:

  • Image recognition

    • Identifying objects in an image.

  • Natural language processing (NLP)

    • Understanding written or vocal speech.

  • Recommendation engines

    • Predicting what similar products a user might like.

Mathematics

Machine learning does not always require having a deep knowledge of math. When it is needed, these are the most relevant mathematical subjects a machine learning expert should be familiar with [2][3]:

  • Linear algebra

  • Statistics

  • Differential calculus

  • Integral calculus

Programming Languages

More than half of all machine learning programs are built using Python. [4] Here are the top 3 programming languages used [4][5]:

  1. Python

  2. R

  3. Java

Graphics Card Vendors

NVIDIA provides the best support for machine learning with its proprietary CUDA library. It is possible to use AMD and Intel graphics cards by using the open source OpenCL library [7] but NVIDIA provides the best performance and compatibility. [6]

Resources

Mathematics [2][3]:

AI Prompt Engineering

Ollama

Ollama is a large language model (LLM) that is the best free and open source alternative to ChatGPT. [8]

Installation [9]:

  • Linux

    $ curl -fsSL https://ollama.com/install.sh | sh

  • macOS

    • Download the latest version here.

Ollama provides many different models. These are categorized by how many billions (B) of parameters the use. The higher the number, the more accurate it is but at the cost of more memory usage. The download size of a model is usually also the minimum size of VRAM needed to run the model. [10]

For PCs, use Ollama 8B for ChatGPT 3.5 quality. It is a 5 GB download. [11]

$ ollama run llama3.1

For phones and low-end hardware, use Ollama 3B which is more efficient while being similar to Ollama 8B. It is a 2 GB download. [12]

$ ollama run llama3.2

For PCs wanting to have image recognition as part of the LLM, use Ollama 11B. It is a 8 GB download. Provide the full path to the image file when chatting with Ollama. [13]

$ ollama run llama3.2-vision

For high-end PCs and ChatGPT 4 quality, use at least Ollama 70B. [14] The community has created smaller bit models (1-bit, 2-bit, and 4-bit). The 1-bit IQ1_M model is not very good. The 4-bit Q4_K_M model is too big for consumer PCs. The 2-bit IQ2_XS model is the best balance of size and reliability. It is a 21 GB download. [15][16]

$ ollama run hf.co/lmstudio-community/Meta-Llama-3-70B-Instruct-GGUF:IQ2_XS

For code programming, the DeepSeek-Coder model is recommended. This is a 9 GB download. [17]

$ ollama run deepseek-coder-v2:16b

Save a conversation to revisit later by using /save <SAVE_NAME>. It will be stored as a new model which can be viewed with /list or the CLI command ollama list. Load the conversation by using /load <SAVE_NAME>.

Exit the LLM instance by typing /bye.

List installed models.

$ ollama list

Delete a model.

  • Linux or macOS

    $ ollama rm <OLLAMA_MODEL>

Delete all models.

  • Linux

    $ sudo rm -r -f /usr/share/ollama/.ollama/models/blobs/
$ sudo rm -r -f /usr/share/ollama/.ollama/models/manifests/

  • macOS

    $ rm -r -f ~/.ollama/models/*

History

Bibliography

  1. “Classification, regression, and prediction - what’s the difference?” Towards Data Science. December 11, 2020. Accessed November 7, 2022. https://towardsdatascience.com/classification-regression-and-prediction-whats-the-difference-5423d9efe4ec

  2. “A beginner’s guide to the math that powers machine learning.” TNW The heart of tech. October 2, 2022. Accessed November 7, 2022. https://thenextweb.com/news/a-beginners-guide-to-the-math-that-powers-machine-learning-syndication

  3. “Math for Machine Learning: 14 Must-Read Books.” Machine Learning Techniques. June 13, 2022. Accessed November 7, 2022. https://mltechniques.com/2022/06/13/math-for-machine-learning-12-must-read-books/

  4. “What is the best programming language for Machine Learning?” Towards Data Science. May 5, 2017. Accessed November 7, 2022. https://towardsdatascience.com/what-is-the-best-programming-language-for-machine-learning-a745c156d6b7

  5. “7 Top Machine Learning Programming Languages.” Codeacademy. October 20, 2021. Accessed November 7, 2022. https://www.codecademy.com/resources/blog/machine-learning-programming-languages/

  6. “How to Pick the Best Graphics Card for Machine Learning.” Towards Data Science. September 19, 2022. Accessed November 7, 2022. https://towardsdatascience.com/how-to-pick-the-best-graphics-card-for-machine-learning-32ce9679e23b

  7. “Does TensorFlow Support OpenCL?” IndianTechWarrior. Accessed November 7, 2022. https://indiantechwarrior.com/does-tensorflow-support-opencl/

  8. “Chatbot Arena LLM Leaderboard: Community-driven Evaluation for Best LLM and AI chatbots.” Chatobt Arena. Accessed December 4, 2024. https://lmarena.ai/

  9. “FAQ.” GitHub ollama/ollama. December 3, 2024. Accessed December 4, 2024. https://github.com/ollama/ollama/blob/main/docs/faq.md

  10. “What does 7b, 8b and all the b’s mean on the models and how are each models different from one another?” Reddit r/LocalLLaMA. May 23, 2024. Accessed December 4, 2024. https://www.reddit.com/r/LocalLLaMA/comments/1cylwmd/what_does_7b_8b_and_all_the_bs_mean_on_the_models/

  11. “Running Llama 3.1 Locally with Ollama: A Step-by-Step Guide.” Medium - Paulo Batista. July 25, 2024. Accessed December 4, 2024. https://medium.com/@paulocsb/running-llama-3-1-locally-with-ollama-a-step-by-step-guide-44c2bb6c1294

  12. “LLaMA 3.2 vs. LLaMA 3.1 vs. Gemma 2: Finding the Best Open-Source LLM for Content Creation.” Medium - RayRay. October 2, 2024. Accessed December 4, 2024. https://byrayray.medium.com/llama-3-2-vs-llama-3-1-vs-gemma-2-finding-the-best-open-source-llm-for-content-creation-1f6085c9f87a

  13. “Llama 3.2 Vision.” Ollama. November 6, 2024. Accessed December 4, 2024. https://ollama.com/blog/llama3.2-vision

  14. “I can now run a GPT-4 class model on my laptop.” Simon Willison’s Weblog. December 9, 2024. Accessed December 12, 2024. https://simonwillison.net/2024/Dec/9/llama-33-70b/

  15. “Running Llama-3-70B gguf on 24gig VRAM.” Reddit r/LocalLLaMA. April 24, 2024. Accessed December 12, 2024. https://www.reddit.com/r/LocalLLaMA/comments/1c7owci/running_llama370b_gguf_on_24gig_vram/

  16. “lmstudio-community/Meta-Llama-3-70B-Instruct-GGUF.” Hugging Face. Accessed December 12, 2024. https://huggingface.co/lmstudio-community/Meta-Llama-3-70B-Instruct-GGUF

  17. “deepseek-coder-v2.” Ollama. September, 2024. Accessed December 13, 2024. https://ollama.com/library/deepseek-coder-v2