DeepLearning.AI TensorFlow Developer Specialization

This repository contains my work and notes from courses in the DeepLearning.AI TensorFlow Developer Specialization on Coursera.

Overview

In this courses, I learned to build and train Convolutional Neural Networks (CNNs) using TensorFlow and Keras. The course involved working with real-world image datasets and implementing neural networks that can recognize patterns in complex visual data.

Key Concepts Covered

• TensorFlow & Keras fundamentals for computer vision tasks
• Implementing CNNs using Conv2D, MaxPooling2D, Dense, Flatten, and Dropout
• Image preprocessing and normalization using Rescaling layers
• Custom training callbacks for early stopping
• Dataset creation using image_dataset_from_directory and tf.data
• Feature map visualization to interpret model behavior
• Real-time image classification using Jupyter widgets

---

🛠️ Tools & Libraries

• TensorFlow / Keras
• Matplotlib
• NumPy
• Ipywidgets (for interactive image upload)
• tf.data.Dataset API

---

Repository Structure

Tensorflow/

• ├── Week1/
• ├── Week2/
• ├── Week3/
• ├── Week4/
• ├── Week5/
• ├── Week6/
• ├── Week7/
• ├── Week8/
• ├── Week9/
• ├── Week10/
• └── README.md

How to Use

1. Clone this repository:

   git clone https://github.com/yourusername/Tensorflow.git
   cd tensorflow
   

2. Install Requiremnents:

   pip install -r requirements.txt
   

Links

• TensorFlow Developer Specialization on Coursera
• https://www.tensorflow.org/api_docs
• https://keras.io/api/

Author

M. Sabtain Khan

• Connect with me on
• Linkedin: https://www.linkedin.com/in/msabtainkhan/
• GitHub : @Sabtain-Dev