TensorFlow Developer Certificate Exam Practice Tests 2024

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Mr Troy

1:10:22

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1 - Getting started

1 - Introduction.mp4

02:19

2 - All resources.html

3 - Questions and concerns.html

2 - Prepare exam environment

4 - Notes.html

5 - Install Python.mp4

02:53

6 - Tip for Mac user.html

7 - Install Pycharm.html

8 - All practice tests.txt

8 - Download practice tests.html

9 - Python packages exam plugin.mp4

05:45

3 - Regression Problems

10 - Linear regression 1question.mp4

02:37

10 - Linear regression 1question.txt

11 - Tip for Windows users.html

12 - Linear regression 1answer.mp4

05:43

12 - Linear regression 1answer.txt

13 - Challenge Linear regression 2question.html

14 - Challenge Linear regression 2answer.html

4 - Image Classification

15 - Grayscale image keras datasetsquestion.mp4

02:23

15 - Grayscale image keras datasetsquestion.txt

16 - Grayscale image keras datasetsanswer.mp4

04:31

16 - Grayscale image keras datasetsanswer.txt

17 - Challenge Grayscale image TF datasetsquestion.html

18 - Challenge Grayscale image TF datasetsanswer.html

19 - Color image Binary classification question.mp4

08:00

19 - Color image Binary classification question.txt

20 - Color image Binary solution.mp4

07:10

20 - Color image Binary solution.txt

21 - Optional Color image binary classificationquestion.html

22 - Optional Color image binary classificationanswer.html

23 - Challenge Color image Multiclassquestion.html

24 - Challenge Color image Multiclassanswer.html

5 - Natural Language Processing

25 - Binary text classificationquestion.mp4

06:21

25 - Binary text classificationquestion.txt

26 - Binary text classificationanswer.mp4

05:04

26 - Binary text classificationanswer.txt

27 - Challenge Binary text classification proportional training sizequestion.html

28 - Challenge Binary text classification proportional training sizeanswer.html

29 - Optional Multiclass text classificationquestion.html

30 - Optional Multiclass text classificationanswer.html

6 - Sequences Time Series and Prediction

31 - Cities humidity forecast question time series.mp4

08:36

31 - Time series question.txt

32 - Cities humidity forecast solution time series.mp4

07:31

32 - Time series solution.txt

33 - Challenge My citys humidity forecast question sequences.html

34 - Challenge My citys humidity forecastanswer sequences.html

7 - Exam procedure

35 - Step by step.html

36 - Share your achievement with the world.mp4

01:29

37 - Summary of Useful Tips.html

Description

Fast-Track to TensorFlow Certification: Practical Tests and Expert Tips for Success

What You'll Learn?

Participants will be thoroughly prepared for the exam with tailored practice tests that closely mimic the format and content of the actual certification exam.
Upon passing the exam, students will be able to add a digital badge to their LinkedIn profiles and join the TensorFlow Certificate Network.
Learners will warm up hands-on experience in TensorFlow by completing practice tests and exercises in real-world scenarios.
Students will regain a deep understanding of TensorFlow fundamentals, including Linear Regression, Image Classification, NLP, and Time Series predictions.

Who is this for?

Aspiring or current AI and machine learning professionals aiming to gain TensorFlow certification.

Individuals with basic programming knowledge and/or a foundational understanding of machine learning concepts.

Developers and students looking for a comprehensive yet concise preparation for the TensorFlow Developer Certificate Exam.

Anyone interested in enhancing their TensorFlow skills and adding a recognized credential to their resume or online profiles.

What You Need to Know?

Basic understanding of any programming language (Python preferred).

It's beneficial if learners have foundational knowledge of machine learning principles.

More details

Description
Welcome to "TensorFlow Developer Certificate Exam Practice Tests 2024 made easy," your efficient path to mastering TensorFlow and preparing for certification. This course will equip you with the knowledge and practical skills needed for the TensorFlow Developer Certificate Exam in a convenient format.
What Makes This Course Effective?
Streamlined Learning: Ideal for those with busy schedules, our focused content is structured to make the most of your time (in less than 2 hours).
Hands-On Practice: Dive into practice tests across key TensorFlow areas like Linear Regression, Image Classification, NLP, and Time Series, crafted to enhance your understanding and proficiency.
Insider Knowledge: Gain insights with expert tips that will help you confidently approach the exam.
Flexible Learning Environment: Choose your preferred learning toolâ€”Google Colab, Jupyter Notebooks, or PyCharmâ€”to work through the content.
Why Choose This Course?
Prepare with Confidence: Our carefully designed practice tests aim to give you a solid grounding in the exam's format and content areas.
Join a Community: Consider joining the TensorFlow Certificate Network to connect with other professionals upon completion.
Showcase Your Skills: Learn how to add a digital badge to your LinkedIn and GitHub profiles to highlight your TensorFlow capabilities.
Enroll in "TensorFlow Developer Certificate Exam Practice Tests 2024 Made Easy" and start building your practical TensorFlow skills today!
Who this course is for:
Aspiring or current AI and machine learning professionals aiming to gain TensorFlow certification.
Individuals with basic programming knowledge and/or a foundational understanding of machine learning concepts.
Developers and students looking for a comprehensive yet concise preparation for the TensorFlow Developer Certificate Exam.
Anyone interested in enhancing their TensorFlow skills and adding a recognized credential to their resume or online profiles.

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TensorFlow

Mr Troy

Instructor's Courses

Mr Troy (Troy Phat Tran) is an Android Engineer based in Adelaide, South Australia, Australia.He is also a Google-certified TensorFlow Developer with a strong passion for AI and deep learning.He holds a Master's degree in Information Technology from St. Paul University Philippines.His research focuses on deep-learning applications for medicinal plant identification on mobile devices.

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