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https://github.com/cricksmaidiene/mids_machine_learning

🤖 A unified repository of coursework fragments from UC Berkeley MIDS ML courses
https://github.com/cricksmaidiene/mids_machine_learning

coursework data-science generative-ai jupyter-notebook machine-learning numpy pandas prompt-engineering scikit-learn spark tensorflow uc-berkeley

Last synced: 30 days ago
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🤖 A unified repository of coursework fragments from UC Berkeley MIDS ML courses

Host: GitHub
URL: https://github.com/cricksmaidiene/mids_machine_learning
Owner: cricksmaidiene
License: mit
Created: 2023-12-26T12:13:14.000Z (about 1 year ago)
Default Branch: main
Last Pushed: 2024-04-16T11:57:28.000Z (9 months ago)
Last Synced: 2024-04-16T14:48:46.016Z (9 months ago)
Topics: coursework, data-science, generative-ai, jupyter-notebook, machine-learning, numpy, pandas, prompt-engineering, scikit-learn, spark, tensorflow, uc-berkeley
Language: Jupyter Notebook
Homepage:
Size: 7.81 MB
Stars: 2
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # Machine Learning @MIDS - UC Berkeley I School  🏫

![](https://img.shields.io/badge/TensorFlow-FF6F00.svg?style=for-the-badge&logo=TensorFlow&logoColor=white)

![](https://img.shields.io/badge/PyTorch-EE4C2C.svg?style=for-the-badge&logo=PyTorch&logoColor=white)

![](https://img.shields.io/badge/scikitlearn-F7931E.svg?style=for-the-badge&logo=scikit-learn&logoColor=white)

![](https://img.shields.io/badge/NumPy-013243.svg?style=for-the-badge&logo=NumPy&logoColor=white)

- [Machine Learning @MIDS - UC Berkeley I School  🏫](#machine-learning-mids---uc-berkeley-i-school--)

  - [📚 Coursework](#-coursework)

  - [📙 Notebooks](#-notebooks)

    - [🖊 Generative AI (`DATASCI 290`)](#-generative-ai-datasci-290)

    - [🤖 Applied Machine Learning (`DATASCI 207`)](#-applied-machine-learning-datasci-207)

    - [📕 Basic Notebooks](#-basic-notebooks)

---

A unified repository of coursework fragments from [UC Berkeley MIDS Program](https://www.ischool.berkeley.edu/programs/mids) 2022-2024. This is a collection of my adapted assignment submissions, classwork notebooks, and other relevant materials. It serves to showcase the scope of work, and also for personal reference.

> 🏗 Under Construction - Notebook Addition in Progress

## 📚 Coursework

I've taken the following core ML courses during my time at MIDS:

- #### 🤖 [DATASCI 207: Applied Machine Learning - Fall 2022](https://ischoolonline.berkeley.edu/data-science/curriculum/applied-machine-learning/)

  - Course Info: Barebones ML, Breadth of Models

  - Course Project: 🍃 [Leafydex - Leaf Classification](https://github.com/cricksmaidiene/leafydex)

- #### ⚡️ [DATASCI 261: Machine Learning at Scale - Spring 2023](https://ischoolonline.berkeley.edu/data-science/curriculum/machine-learning-at-scale/)

  - Course Info: Data Engineering & Model Training with Apache Spark

  - Course Project: 🛬 [US Flight Delay Prediction](https://github.com/cricksmaidiene/flight_delay_prediction)

- #### 📰 [DATASCI 266: Natural Language Processing - Fall 2023](https://ischoolonline.berkeley.edu/data-science/curriculum/natural-language-processing/)

  - Course Info: Neural Network Models with Transformers

  - Course Project: 🏂 [Snowplough - News Topic Classification & Bias Analysis](https://github.com/cricksmaidiene/snowplough)

- #### 🖊 [DATASCI 290: Generative AI - Spring 2024](https://www.ischool.berkeley.edu/courses/datasci/290/genai)

  - Course Info: LLMs, Stable Difussion, RAGs, Prompt Engineering

## 📙 Notebooks

### 🖊 Generative AI (`DATASCI 290`)

| Notebook | Description |

| --- | --- |

| [Stable Diffusion & Image Validation](./src/generative_ai/stable_diffusion_and_image_validation_mids_290_gen_ai.ipynb) | Multimodal image generation and captioning with `diffusers`, `CLIP`, `BLIP` and `Llava` |

| [Prompt Engineering](./src/generative_ai/prompt_engineering_mids_290_gen_ai.ipynb) | Prompt Engineering Examples with `Mistral7B` |

| [Retrieval Augmented Generation Proof-of-Concept](./src/generative_ai/retrieval_augmented_generation_poc.ipynb) | Google Colab notebook and report using `Mistal7B`, `Cohere` and `Qdrant` to develop a simple RAG system and iterate on performance |

### 🤖 Applied Machine Learning (`DATASCI 207`)

| Notebook | Description |

| --- | --- |

| [Introduction to Supervised Learning](./src/applied_ml/datasci_207_notebook_01.ipynb) | Road to Linear Regression with `Generalization` and `MSE` (Mean Squared Error) calculation |

### 📕 Basic Notebooks

| Notebook | Description |

| --- | --- |

| [PyTorch Introduction](./src/neural_networks/pytorch_introduction.ipynb) | A basic introduction to tensors, classes, and operations in PyTorch |