This repository contains a collection of machine learning projects developed by [Your Name].

• Description: A simple Python program to convert temperatures from Celsius to Fahrenheit.
• File: celsius_to_fahrenheit.py
• Usage: Run the script and input the temperature in Celsius to get the converted temperature in Fahrenheit.

• Description: A machine learning project predicting diabetes using classification algorithms.
• Files:
  • diabetes_prediction.ipynb: Jupyter Notebook containing the analysis, data preprocessing, and model building.
  • diabetes_data.csv: Dataset used for prediction.

• Description: Machine learning models to predict the likelihood of heart disease.
• Files:
  • heart_disease_prediction.ipynb: Jupyter Notebook containing data analysis, preprocessing, model building, and evaluation.
  • heart_disease_data.csv: Dataset used for heart disease prediction.

• Description: Image classification using the Fashion MNIST dataset to categorize clothing articles.
• Files:
  • classifying_clothes.ipynb: Jupyter Notebook encompassing data exploration, model development using deep learning (e.g., TensorFlow, PyTorch), and evaluation.
  • tensorflow dataset - fashion_mnist: Dataset containing fashion items' grayscale images for classification.

• Description: Image classification distinguishing between cats and dogs using Convolutional Neural Networks (CNN). The dataset was loaded directly from TensorFlow Datasets (tfds).
• Files:
  • cats_vs_dogs.ipynb: Jupyter Notebook implementing CNN for classifying cats and dogs. Data loaded using tfds.

• Description: Classifying cats and dogs using transfer learning with MobileNet pre-trained model. The dataset was loaded directly from TensorFlow Datasets (tfds).
• Files:
  • Transfer_Learning_on_CatsVsDogs.ipynb: Jupyter Notebook applying transfer learning using MobileNet for cats and dogs classification. Data loaded using tfds.

• Description: Image classification of different flowers using Convolutional Neural Networks (CNN). The dataset was loaded directly from TensorFlow Datasets (tfds).
• Files:
  • Flower_Classification.ipynb: Jupyter Notebook for flower classification using CNN. Data loaded using tfds.

• Description: Flower classification using transfer learning with a CNN architecture. The dataset was loaded directly from TensorFlow Datasets (tfds).
• Files:
  • Flower_Classification_using_TL.ipynb: Jupyter Notebook for flower classification using transfer learning. Data loaded using tfds.

• Description: Predicting whether someone who apply for loan will get loan or not.
• Files:
  • loan_aprooval.ipynb: Jupyter Notebook for load approval.

• Description: Classic project of customer churn prediction using kaggle dataset.
• Files:
  • customer-churn-96-acc-gradient-boosting.ipynb: Jupyter Notebook for Customer Churn Prediction.

• Breast Cancer Detection
• Stock Price Prediction
• Image Classification using CNN

Stay tuned for more projects and updates!

Feel free to explore each project for detailed information, code, and datasets.