TensorFlow fundamentals
- Offered byMicrosoft
TensorFlow fundamentals at Microsoft Overview
Duration | 4 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Beginner |
Official Website | Explore Free Course  |
Credential | Certificate |
TensorFlow fundamentals at Microsoft Course details
- Introduction to TensorFlow using Keras
- Introduction to computer vision with TensorFlow
- Introduction to natural language processing with TensorFlow
- Introduction to audio classification with TensorFlow
- Going beyond Keras - customizing with TensorFlow
- Learn the fundamentals of deep learning with TensorFlow
- This beginner friendly learning path will introduce key concepts to building machine learning models
- This module provides all the concepts and practical knowledge you need to get started with TensorFlow
- We'll explore Keras, a high-level API released as part of TensorFlow, and we'll use it to build a simple neural network for image classification
- In this course, you will get an introduction to Computer Vision using TensorFlow
- We'll use image classification to learn about convolutional neural networks, and then see how pre-trained networks and transfer learning can improve our models and solve real-world problems
TensorFlow fundamentals at Microsoft Curriculum
Introduction to TensorFlow using Keras
Introduction
Data
Neural network architecture
Training and testing the neural network
Making a prediction
Summary
Introduction to computer vision with TensorFlow
Introduction
Introduction to image data
Training a dense neural network
Multi-layer networks
Convolutional neural networks
Pretrained models and transfer learning
Summary
Introduction to natural language processing with TensorFlow
Introduction to natural language processing with TensorFlow
Representing text as Tensors
Represent words with embeddings
Capture patterns with recurrent neural networks
Generate text with recurrent networks
Check your knowledge
Summary
Introduction to audio classification with TensorFlow
Introduction
Understanding audio data
Visualizing and transforming data
Build the model
Summary
Going beyond Keras - customizing with TensorFlow
Introduction
Tensors and variables
Automatic differentiation
Build the model
Training and testing the neural network
Eager execution and graph execution
Making a prediction
Summary
TensorFlow fundamentals at Microsoft Entry Requirements
- Basic Python knowledgeBasic knowledge about how to use Jupyter NotebooksBasic understanding of machine learning
- Not mentioned
TensorFlow fundamentals at Microsoft Admission Process
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