https://github.com/eftekin/ai-engventures
🤖 A collection of projects and experiences in AI engineering, including machine learning, NLP, and computer vision.
https://github.com/eftekin/ai-engventures
ai computer-vision deep-learning image-processing machine-learning
Last synced: 9 months ago
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🤖 A collection of projects and experiences in AI engineering, including machine learning, NLP, and computer vision.
- Host: GitHub
- URL: https://github.com/eftekin/ai-engventures
- Owner: eftekin
- License: mit
- Created: 2024-04-20T21:55:49.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-02-16T20:31:35.000Z (over 1 year ago)
- Last Synced: 2025-02-28T16:51:55.353Z (over 1 year ago)
- Topics: ai, computer-vision, deep-learning, image-processing, machine-learning
- Language: Jupyter Notebook
- Homepage:
- Size: 62.3 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 🚀 AI EngVentures
Welcome to the **AI EngVentures** repository! This repo is a collection of my explorations, projects, and insights in artificial intelligence, computer vision, image processing, and machine learning. Through various projects and topics, I aim to deepen my understanding and share my learnings in these fields.
## 🗂️ Contents
### 1. 🤖 [Machine Learning](./machine_learning)
Dive into feature engineering, supervised learning, and upcoming unsupervised learning models:
- **Feature Engineering**: Techniques for transforming and scaling data.
- **Supervised Learning**: Projects covering linear regression, logistic regression, and k-nearest neighbors algorithms.
- **Unsupervised Learning** Projects featuring K-Means clustering, PCA (Principal Component Analysis), and more.
### 2. 🛠️ [Projects](./projects)
Real-world applications of AI and machine learning techniques:
- **🩺 [Cancer Classifier](./projects/supervised_learning/cancer_classifier)**: A model to predict cancer based on diagnostic data.
- **🍯 [Honey Production](./projects/supervised_learning/honey_production)**: Predicting honey production using regression techniques.
- **💳 [Credit Card Fraud Detection](./projects/supervised_learning/predict_credit_card_fraud)**: Identifying fraudulent transactions with logistic regression.
- **🎾 [Tennis Ace](./projects/supervised_learning/tennis_ace)**: A project exploring data analysis in sports.
- **🚩 [Find the Flag!](./projects/supervised_learning/find_the_flag)**: Predict the continent of a flag using decision trees and features like colors and shapes. [Dataset](https://archive.ics.uci.edu/ml/datasets/Flags)
- **🧰 [Transforming Data into Features](./projects/feature_engineering/transforming_data)**: Transform customer review data by scaling, encoding categorical variables, and handling date-time features. [Dataset from Kaggle](https://www.kaggle.com/datasets/nicapotato/womens-ecommerce-clothing-reviews).
- **📝 [Wrapper Methods](./projects/feature_engineering/wrapper_methods)**: Use logistic regression to predict obesity and explore feature selection with wrapper methods. Dataset: [Obesity Data Set](https://archive.ics.uci.edu/dataset/544/estimation+of+obesity+levels+based+on+eating+habits+and+physical+condition).
- **✍️ [Handwriting Recognition](./projects/unsupervised_learning/handwriting_recognition_kmeans)**: Use K-means clustering to recognize and group images of handwritten digits, leveraging scikit-learn for clustering analysis. [Dataset from scikit-learn](https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html).
- **📧 [Email Similarity Classification](./projects/supervised_learning/email_similarity)**: A project that classifies emails into categories (hardware or hockey) using the Naive Bayes algorithm. This project utilizes the `fetch_20newsgroups` dataset and includes functionalities for predicting email categories based on user input.
- **🍷 [Predict Wine Quality with Regularization](./projects/supervised_learning/predict_wine_quality)**: Classify wine quality (good/bad) with logistic regression, ridge, and lasso regularization. [Wine Quality Dataset](https://archive.ics.uci.edu/ml/datasets/Wine+Quality)
- **🌲 [Random Forests Project](./projects/supervised_learning/random_forests)**: Predict income >$50K from census data. [Dataset](https://archive.ics.uci.edu/ml/datasets/census+income)
- **🔧 [Building ML Pipelines](./projects/machine_learning/ml_pipelines)**: Pipeline for pediatric bone marrow transplants, including preprocessing and classifier selection to predict survival.
### 3. 🖼️ [Computer Vision and Image Processing](./computer_vision_and_image_processing)
Explore core concepts of image processing and computer vision, covering topics such as:
- **Image Processing Fundamentals** (Filtering, edge detection)
- **Geometric Transformations**
- **Pixel Transformations**
- **Object Detection**
- **Logistic Regression for Vision Tasks**
- **Neural Networks for Vision Applications**
### 4. 📐 [Math for AI Engineering](./math_for_ai_engineering)
Understand the mathematical foundations required for AI, including:
- **Linear Algebra**
- **Probability**
- **Statistics**
## 🤝 How to Contribute
If you'd like to contribute:
1. Fork this repository.
2. Create a new branch.
3. Make your changes and submit a pull request.
I'm open to contributions and feedback, so feel free to reach out with any ideas!