Master TensorFlow and Deep learning — from basic neural networks to advanced models and real world AI applications.
Sub Category
- Data Science
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Objectives
- 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.
Pre Requisites
- No prior deep learning experience required.
FAQ
- Q. How long do I have access to the course materials?
- A. You can view and review the lecture materials indefinitely, like an on-demand channel.
- Q. Can I take my courses with me wherever I go?
- A. Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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