https://github.com/abdul-rafay19/internintelligence_machinelearningintern
A collection of hands-on projects completed during my Machine Learning Virtual Internship at Intern Intelligence. Includes hyperparameter tuning using Scikit-Learn and Optuna, and deep learning model development for image and text data using TensorFlow, Keras, and PyTorch.
https://github.com/abdul-rafay19/internintelligence_machinelearningintern
ai algorithm algorithms artificial-intelligence intelligence intern-intelligence internship machine-learning machine-learning-algorithms machinelearning programming programming-language python pytorch sckit-learn tenserflow
Last synced: 23 days ago
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A collection of hands-on projects completed during my Machine Learning Virtual Internship at Intern Intelligence. Includes hyperparameter tuning using Scikit-Learn and Optuna, and deep learning model development for image and text data using TensorFlow, Keras, and PyTorch.
- Host: GitHub
- URL: https://github.com/abdul-rafay19/internintelligence_machinelearningintern
- Owner: abdul-rafay19
- Created: 2025-04-04T10:54:08.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-04-20T17:14:54.000Z (7 months ago)
- Last Synced: 2025-04-20T18:26:38.365Z (7 months ago)
- Topics: ai, algorithm, algorithms, artificial-intelligence, intelligence, intern-intelligence, internship, machine-learning, machine-learning-algorithms, machinelearning, programming, programming-language, python, pytorch, sckit-learn, tenserflow
- Language: Jupyter Notebook
- Homepage:
- Size: 1.99 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🤖 Machine Learning Virtual Internship @ Intern Intelligence
**Author:** Abdul Rafay
**Degree:** BS Software Engineering
---
## 📌 Overview
I am currently doing a **Machine Learning Virtual Internship** at **Intern Intelligence**, focusing on advanced machine learning techniques, deep learning, model optimization, and real-world applications using tools like **Scikit-Learn**, **TensorFlow**, and **PyTorch**.
---
## ✅ Internship Tasks
### 🔧 TASK 1: Model Hyperparameter Tuning
**Objective:** Optimize the hyperparameters of a machine learning model to enhance performance.
- **Model Selection:** Random Forest, XGBoost, etc.
- **Techniques Used:** Grid Search, Random Search, Optuna
- **Evaluation Metrics:** Accuracy, Precision, Recall, F1 Score
- **Tools:** Scikit-Learn, Optuna, Google Colab
---
### 🧠 TASK 2: Deep Learning Model Development
**Objective:** Build and train a deep learning model for complex tasks like image classification or NLP.
- **Data Preparation:** Images / Text preprocessing
- **Model Architecture:** CNNs, RNNs, LSTMs
- **Frameworks:** TensorFlow, Keras, PyTorch
- **Evaluation Metrics:** Accuracy, Precision, Recall, Loss
- **Deployment:** Integration into applications
---
## 🛠 Technologies & Tools
- Python, Scikit-Learn, Optuna, XGBoost, RandomForestClassifier
- TensorFlow, Keras, PyTorch, NumPy, Pandas, Matplotlib, Seaborn
- Google Colab, Jupyter Notebook, Hugging Face, TensorFlow Hub, PyTorch Hub
- Streamlit, Flask (for deployment)
---
> “Every step forward is a step closer to excellence—learning never stops.”
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🔗 [Connect with me on LinkedIn](https://www.linkedin.com/in/abdul-rafay19)