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Course Curriculum

Introduction
1.1 Accuracy of a model 00:00:00
1.2 Balancing a dataset 00:00:00
1.3 Commenting on the results 00:00:00
1.4 Creating the batching class 00:00:00
1.5 Early stopping and batching preparation 00:00:00
1.6 Homework 00:00:00
1.7 How to tackle the MNIST dataset 00:00:00
1.8 Installing the TensorFlow package 00:00:00
1.9 Laying down the model 00:00:00
1.10 Laying down the optimizers 00:00:00
1.11MNIST – Declaring the loss 00:00:00
1.12 MNIST – Importing libraries and data 00:00:00
1.13 MNIST – Outlining the model 00:00:00
1.14 MNIST dataset 00:00:00
1.15 Optimization 00:00:00
1.16 Optimizing the algorithm 00:00:00
1.17 Outlining the model 00:00:00
1.18 Outlining the solution 00:00:00
1.19 Output 00:00:00
1.20 Running the code 00:00:00
1.21 TensorFlow introduction 00:00:00
1.22 Test 00:00:00
1.23 Types of file formats in TensorFlow and data handling 00:00:00

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  • 1 week, 3 days
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