TensorFlow: Introduction to Machine Learning
TensorFlow
| Intermediate
- 19 Videos | 1h 40m 26s
- Includes Assessment
- Earns a Badge
Explore the concept of machine learning in TensorFlow, including TensorFlow installation and configuration, the use of the TensorFlow computation graph, and working with building blocks.
WHAT YOU WILL LEARN
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describe kinds of machine learning algorithms and their use casesdefine the training and prediction phases in machine learningdefine the conceptual differences between traditional machine learning and deep learningcompare and contrast supervised and unsupervised techniques in machine learningdefine the advantages and challenges in using TensorFlow for machine learningdistinguish data and computations as distinct building blocks of a TensorFlow computation graphchoose the right way to install TensorFlow based on the user's environmentinstall TensorFlow and work with Jupyter Notebooksspecify constants and build and run a computation graph
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use TensorBoard to visualize the computation graphbuild and execute a computation graph with variables and placeholdersvisualize variables and placeholders on TensorBoardrecognize how variables are trainable parameters and can be updated within a sessionwork with feed dictionaries to input data to placeholders during traininguse named scopes to group computationsspecify and work with eager execution for prototyping and developmentrecall basic concepts of machine learning and TensorFlowbuild and execute computation graphs with computation nodes and data
IN THIS COURSE
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1.Course Overview2m 9sUP NEXT
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2.Introduction to Machine Learning Algorithms8m 21s
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3.Understanding Machine Learning8m 47s
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4.Understanding Deep Learning3m 42s
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5.Supervised and Unsupervised Learning4m 25s
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6.TensorFlow for Machine Learning4m 52s
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7.Tensors and Operators7m 48s
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8.Understanding How to Install TensorFlow5m 42s
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9.Installing TensorFlow on the Local Machine3m 57s
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10.Working with Constants8m 51s
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11.The Computation Graph with TensorBoard2m 37s
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12.Working with Variables and Placeholders8m 1s
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13.Variables and Placeholders on TensorBoard2m 45s
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14.Updating Variables in a Session4m 40s
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15.Feed Dictionaries7m 46s
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16.Named Scopes for Better Visualization2m 25s
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17.Eager Execution4m 46s
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18.Exercise: Machine Learning and TensorFlow5m 9s
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19.Exercise: Working with Computation Graph3m 45s
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