segzee Goto Github PK

AI Programming with Python Project One: Dog Breed Identifier

Overview This project focuses on utilizing a pre-trained image classifier to build a web app that identifies dog breeds from uploaded images. The primary objective is to enhance the user experience by incorporating a machine learning model capable of accurately classifying dog breeds.

Features

• Pre-trained Model Integration: Incorporate a pre-trained image classifier to accurately identify dog breeds.

• Web Application: Develop a user-friendly web app allowing users to upload images and receive real-time predictions of dog breeds.

• Interactive Interface: Provide an interactive interface for users to explore predictions, view confidence scores, and gain insights into the classification process.

AI Programming with Python Project two: Train a convolutional neural network (CNN) to classify images of flowers

Overview In this project, the objective is to train a convolutional neural network (CNN) to classify images of flowers. This hands-on project empowers me to build and fine-tune the image classifier, enhancing my understanding of deep learning concepts.

Features

• Custom Image Classifier: Train a CNN to classify various flower species from images.

• Transfer Learning: Explore transfer learning techniques to leverage pre-trained models and improve classification performance.

• Model Evaluation: Assess the model's accuracy, precision, recall, and other relevant metrics.

AWS Machine Learning Fundamentals Projects

1. Predict Bike Sharing Demand with AutoGluon Overview Predict bike sharing demand using AutoGluon, a machine learning framework that automates the model selection and hyperparameter tuning process. This project aims to optimize the prediction accuracy for bike rental demand.

2. Developing Handwritten Digits Classifier with PyTorch Overview Train a deep neural network using PyTorch to classify handwritten digits. This project focuses on building a robust digit classifier for various applications, such as digit recognition in real-world scenarios.

3. Landmark Classification & Tagging for Social Media Overview Build a landmark classification and tagging system for social media images. This project involves training a model to recognize landmarks in images and automatically adding relevant tags.

4. Build a ML Workflow for Scones Unlimited on Amazon SageMaker Overview Create a machine learning workflow for Scones Unlimited using Amazon SageMaker. This project involves data preprocessing, model training, and deployment on the SageMaker platform to enhance business processes.

Contributing If you wish to contribute to any of the projects, you are welcome to do so

Acknowledgments I express gratitude to Udacity, and AWS team for providing powerful tools and frameworks.