This repository contains my projects and hands-on labs from the TensorFlow Developer Specialization by Laurence Moroney. It demonstrates practical deep learning implementations using TensorFlow and covers key areas like computer vision, natural language processing, and time series forecasting.
The repository is organized by courses from the specialization:
-
Intro to TensorFlow for AI, ML, and DL
- Basics of TensorFlow and model building
- Data pipelines, datasets, and preprocessing
- Training simple neural networks
-
Convolutional Neural Networks in TensorFlow
- Image classification with CNNs
- Data augmentation and regularization techniques
- Transfer learning with pre-trained models
-
Natural Language Processing in TensorFlow
- Text preprocessing and tokenization
- Word embeddings and sequence models
- Sentiment analysis and text classification
-
Time Series Forecasting in TensorFlow
- Building RNNs and LSTMs for time series data
- Multi-step forecasting and evaluation
- Handling real-world datasets
- End-to-end implementations for each course project
- Clean and organized folder structure per course
- Ready-to-run notebooks for hands-on practice
- Demonstrates TensorFlow best practices and workflows
tensorflow_developer_specialization/
├── README.md
├── Intro to TensorFlow/
├── ConvNet in TensorFlow/
├── NLP in TensorFlow/
└── Time Series in TensorFlow/
This repository is a personal portfolio of projects to showcase my TensorFlow skills, ready for reference or further experimentation.
Let's Learning !!