What You'll Learn
- Introduction to TensorFlow and its ecosystem.
- Setting up TensorFlow (installation, virtual environments).
- TensorFlow Core Concepts: Tensors, Variables, Operations.
- Understanding the TensorFlow Execution Model.
- Working with Tensors: Creating, Manipulating, and Indexing.
- Mathematical Operations and Broadcasting.
- Variables and Constants.
- Automatic Differentiation with GradientTape.
- Compiling and Training Keras Models.
- Model Evaluation and Performance Metrics.
- Convolutional Layers, Pooling Layers, and Activation Functions.
- Building CNNs for Image Classification and Object Detection.
- Understanding Sequence Data and Time Series Analysis.
- Building RNNs for Text Generation and Sentiment Analysis.
- Text Preprocessing: Tokenization, Stemming, and Lemmatization.
- TensorFlow Datasets API for Efficient Data Loading.
- TensorBoard for Visualization and Debugging.
- TensorFlow Lite for Mobile and Embedded Devices.
- TensorFlow.js for Browser Based Machine Learning.
Requirements
- No prior deep learning experience required.
Who This Course is For
- Anyone curious about AI and deep learning who wants to start from scratch.
- Those with Python knowledge who want to dive into TensorFlow and neural networks.
- rofessionals aiming to enhance their ML/DL skills with TensorFlow.
- Learners who want to explore advanced neural architectures and applications.
Your Instructor
Brighter Futures Hub
Instructor at Udemy
4.0 Instructor Rating
466 Reviews
34,241 Students
32 Courses
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