https://github.com/shimul-zahan/ml-bootcamp
A personal learning repository for mastering Machine Learning concepts and techniques. It includes practical projects, hands-on exercises, and solutions covering topics such as regression, classification, neural networks, NLP, and more, using Python and popular ML libraries like scikit-learn, TensorFlow, and pandas.
https://github.com/shimul-zahan/ml-bootcamp
classification data-science deep-learning machine-learning machine-learning-algorithms neural-networks nlp-machine-learning projects regression
Last synced: 4 months ago
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A personal learning repository for mastering Machine Learning concepts and techniques. It includes practical projects, hands-on exercises, and solutions covering topics such as regression, classification, neural networks, NLP, and more, using Python and popular ML libraries like scikit-learn, TensorFlow, and pandas.
- Host: GitHub
- URL: https://github.com/shimul-zahan/ml-bootcamp
- Owner: Shimul-Zahan
- License: mit
- Created: 2025-01-10T16:42:24.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-22T08:15:15.000Z (over 1 year ago)
- Last Synced: 2025-04-12T17:53:22.786Z (about 1 year ago)
- Topics: classification, data-science, deep-learning, machine-learning, machine-learning-algorithms, neural-networks, nlp-machine-learning, projects, regression
- Language: Jupyter Notebook
- Homepage:
- Size: 76.8 MB
- Stars: 1
- Watchers: 1
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
- Support: Support Vector Machine/SVM_Classification_README.md
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README
# ML Bootcamp
Welcome to the **ML Bootcamp** repository! This repository is a personal learning hub where I document my progress, projects, and notes related to Machine Learning. It includes hands-on exercises, code snippets, and solutions to various ML problems as I explore different concepts and techniques.
## About
This repository serves as a learning and practice space for foundational and advanced Machine Learning topics. By building projects and solving practical problems, I aim to strengthen my understanding of:
- Data preprocessing and feature engineering
- Supervised and unsupervised learning algorithms
- Deep learning concepts and neural networks
- Natural language processing (NLP)
- Time series forecasting and clustering techniques
## Topics Covered
- Linear Regression and Logistic Regression
- Decision Trees and Random Forests
- Support Vector Machines (SVM)
- Neural Networks and Deep Learning
- Convolutional Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs) and LSTMs
- Text Classification and Sentiment Analysis
- Data Visualization and EDA (Exploratory Data Analysis)
## Tools and Technologies
- Python
- Jupyter Notebooks
- Scikit-Learn
- TensorFlow / Keras
- pandas
- NumPy
- Matplotlib / Seaborn
## How to Use
1. Clone the repository:
```bash
git clone https://github.com/yourusername/ML-Bootcamp.git
```
2. Navigate to the project folder:
```bash
cd ML-Bootcamp
```
3. Install the required dependencies:
```bash
pip install -r requirements.txt
```
4. Explore project folders and notebooks for learning materials.
## Contribution
This repository is primarily for personal learning, but suggestions and improvements are welcome. Feel free to fork, explore, and build upon it.
## License
This repository is licensed under the MIT License.