Deeplearning.AI TensorFlow Advanced Techniques Specialization Solution

This repository contains my solutions for the Coursera course TensorFlow: Advanced Techniques Specialization. Expand your knowledge of the Functional API and build exotic non-sequential model types. Learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions. Explore generative deep learning including the ways AIs can create new content from Style Transfer to Auto Encoding, VAEs, and GANs.

Tensorflow Advanced Technique Specialization - Solution

This project aims to develop an accurate and robust model for classifying and detecting damages on vehicles. The project utilizes the Mask R-CNN architecture implemented using TensorFlow. By leveraging advanced computer vision techniques, this project provides a comprehensive solution for automating the identification and localization of damages

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This is my solution to the TensorFlow: Advanced Techniques Specialization course on coursera

Tensorflow and Keras solution to the House Prices: Advanced Regression Techniques dataset on Kaggle

This repository features my projects on speech recognition and audio classification. Explore solutions for music genre classification, speaker recognition, and emotion detection using advanced ML techniques with TensorFlow and scikit-learn. Dive into the code and documentation to learn more!

: A comprehensive collection of computer vision projects demonstrating my progression from foundational image processing techniques to advanced applications using deep learning. Built with Python, OpenCV, TensorFlow, and PyTorch, this repository highlights practical implementations and innovative solutions in the field of computer vision

This repository contains a deep learning-based solution for segmenting the optic disc and optic cup in fundus images using TensorFlow and Keras. The project utilizes advanced image processing techniques and incorporates a U-Net architecture for efficient segmentation.

Exploring advanced deep learning techniques and optimizing neural network architectures! Passionate about model efficiency, hyperparameter tuning, and leveraging frameworks like TensorFlow and PyTorch for scalable AI solutions. Always eager to refine workflows and push the boundaries of performance. Let me know if you’d like any adjustments! 🚀

This cutting-edge deep learning project develops a sophisticated machine learning model for classifying kidney diseases using advanced medical imaging techniques. By leveraging state-of-the-art technologies like TensorFlow, Keras, DVC, and MLFlow, we've created a robust solution for automated medical image analysis.