Janani Ravi (et al.) | Duration: 13h 00m | Video: H264 1280x720 | Audio: AAC 48 kHz 2ch | 2,02 GB | Language: English
Google released TensorFlow 2.0 in October 2019 which uses the dynamic graph and is more Python friendly. There are multiple changes to ensure removal of redundant APIs and better integration with Python runtime and Eager Execution.
* Learn everything you need to know to get started with Tensorflow 2.0.
* Step up your TensorFlow understanding by learning how to design data pipelines and implement hyperparameter tuning for Tensorflow 2.0.
* Learn how to build a machine learning workflow with Keras and work with time series data to generate high performing forecasts and predictions.
Courses in this path
A1. Getting Started with TensorFlow 2.0 (Janani Ravi, 2020)
B1. Designing Data Pipelines with TensorFlow 2.0 (Chase DeHan, 2020)
B3. Building Machine Learning Solutions with TensorFlow.js (Abhishek Kumar, 2020)
C1. Build a Machine Learning Workflow with Keras TensorFlow 2.0 (Janani Ravi, 2020)
C2. Implement Time Series Analysis, Forecasting and Prediction with TensorFlow 2.0 (Chase DeHan, 2020)
Homepage
https://www.pluralsight.com/paths/building-machine-learning-solutions-with-tensorflow-20
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