This repository contains all my completed assignments, notes, and certificate from the TensorFlow in Practice Specialization by DeepLearning.AI on Coursera.
✅ All programming assignments are completed by me as part of my personal learning journey.
📗 Course 1: Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
- Learn TensorFlow fundamentals and best practices
- Build and train simple neural networks
- Apply deep learning principles using real-world datasets
- Gain practical experience with TensorFlow tools
- Work with image data and computer vision tasks
- Understand and visualize how convolutions extract features
- Use data augmentation and dropout to prevent overfitting
- Apply transfer learning from pre-trained models
- Preprocess and tokenize raw text input
- Convert text to vectors for training
- Use RNNs, GRUs, and LSTMs to model sequences
- Train a text generator using LSTM layers
- Prepare time series data for modeling
- Apply RNNs and 1D Convolutional Networks for forecasting
- Implement best practices for sequence learning
- Build a sunspot prediction model using real data
This repository is licensed under the MIT License.
All four courses were completed as part of the TensorFlow Developer Professional Certificate on Coursera. The official certificates are available in the Certificates/ folder.