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Courses>log>Applied Machine Learning: Industry Case Study with TensorFlow
Applied Machine Learning: Industry Case Study with TensorFlow
Price:Paid
Length:3 hours
Content type:text
level:intermediate
Language:English
Updated:21 August 2022
Published:13 April 2022
Similar courses
Opportunities
Courses>>Applied Machine Learning: Industry Case Study with TensorFlow
Applied Machine Learning: Industry Case Study with TensorFlow
 English
 Adaptilab
DescriptionIn this course, you'll work on an industry-level machine learning project based on predicting weekly retail sales given different factors. You will learn the most efficient techniques used to train and evaluate scalable machine learning models. After completing this course, you will be able to take on industry-level machine learning projects, from data analysis to creating efficient models and providing results and insights. The code for this course is built around the TensorFlow framework, which is one of the premier frameworks for industry machine learning, and the Python pandas library for data analysis. Basic knowledge of Python and TensorFlow are prerequisites. To get some experience with TensorFlow, try our course: Machine Learning for Software Engineers. This course was created by AdaptiLab, a company specializing in evaluating, sourcing, and upskilling enterprise machine learning talent. It is built in collaboration with industry machine learning experts from Google, Microsoft, Amazon, and Apple.
Syllabus

1. Overview

1. Introduction

2. The Dataset

3. Missing Data

4. Dropping Features

5. Filling In Data

6. Merging Data

7. Categorical Data

8. Scatter Plot

9. Bar Plot

10. Interpreting Plots

11. Quiz

1. Introduction

2. Splitting Datasets

3. Integer Features

4. Float Features

5. String Features

6. Writing TFRecords

7. Example Spec

8. Parsing Examples

9. TFRecords Dataset

10. Numeric Columns

11. Indicator Columns

12. Embedding Columns

13. Model Input Layer

14. Quiz

1. Introduction

2. Model Layers

3. Regression Function

4. Training Mode

5. Evaluation Mode

6. Prediction Mode

7. Regression Model

8. Model Training

9. Model Evaluation

10. Making Predictions

11. Final Report

12. Course Conclusion

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Careertail
Courses>log>Applied Machine Learning: Industry Case Study with TensorFlow
Applied Machine Learning: Industry Case Study with TensorFlow
Price:Paid
Length:3 hours
Content type:text
level:intermediate
Language:English
Updated:21 August 2022
Published:13 April 2022
Similar courses
Opportunities
Courses>>Applied Machine Learning: Industry Case Study with TensorFlow
Applied Machine Learning: Industry Case Study with TensorFlow
 English
 Adaptilab
DescriptionIn this course, you'll work on an industry-level machine learning project based on predicting weekly retail sales given different factors. You will learn the most efficient techniques used to train and evaluate scalable machine learning models. After completing this course, you will be able to take on industry-level machine learning projects, from data analysis to creating efficient models and providing results and insights. The code for this course is built around the TensorFlow framework, which is one of the premier frameworks for industry machine learning, and the Python pandas library for data analysis. Basic knowledge of Python and TensorFlow are prerequisites. To get some experience with TensorFlow, try our course: Machine Learning for Software Engineers. This course was created by AdaptiLab, a company specializing in evaluating, sourcing, and upskilling enterprise machine learning talent. It is built in collaboration with industry machine learning experts from Google, Microsoft, Amazon, and Apple.
Syllabus

1. Overview

1. Introduction

2. The Dataset

3. Missing Data

4. Dropping Features

5. Filling In Data

6. Merging Data

7. Categorical Data

8. Scatter Plot

9. Bar Plot

10. Interpreting Plots

11. Quiz

1. Introduction

2. Splitting Datasets

3. Integer Features

4. Float Features

5. String Features

6. Writing TFRecords

7. Example Spec

8. Parsing Examples

9. TFRecords Dataset

10. Numeric Columns

11. Indicator Columns

12. Embedding Columns

13. Model Input Layer

14. Quiz

1. Introduction

2. Model Layers

3. Regression Function

4. Training Mode

5. Evaluation Mode

6. Prediction Mode

7. Regression Model

8. Model Training

9. Model Evaluation

10. Making Predictions

11. Final Report

12. Course Conclusion

Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot