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Justin Flett

TensorFlow is a widely-used data science and machine learning software library. This course will teach you the basics of implementing predictive analytics using TensorFlow, including supervised learning, recommendation, and reinforcement systems.

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TensorFlow is a widely-used data science and machine learning software library. This course will teach you the basics of implementing predictive analytics using TensorFlow, including supervised learning, recommendation, and reinforcement systems.

Data Science and Machine Learning are rapidly growing fields that use scientific methods and processes to extract useful knowledge and insights from data. In this course, Implementing Predictive Analytics with TensorFlow, you will learn foundational knowledge of solving real-world data science problems. First, you will explore the basics of implementing supervised learning problems including linear regression and neural networks. Next, you will discover how recommendation systems can be implemented using TensorFlow. Finally, you will learn how to understand and implement reinforcement learning systems. When you are finished with this course, you will have the skills and knowledge of TensorFlow needed to solve data science and machine learning problems.

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What's inside

Syllabus

Course Overview
Implementing Supervised Learning Systems
Implementing Recommendation Systems
Implementing Reinforcement Learning Systems
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Builds a strong foundation for learners whose background includes programming and some data science knowledge
Teaches skills, knowledge, and tools that are highly relevant to industry
Develops professional skills or deep expertise in a particular topic or set of topics
Teaches tools or software that are on the decline or no longer widely used in industry
Requires learners to come in with extensive background knowledge first
Teaches material that may be dated by software updates

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Implementing Predictive Analytics with TensorFlow with these activities:
Review TensorFlow Tutorial
Reviewing the TensorFlow tutorials will help to refresh your knowledge and understanding of the basics of TensorFlow, which will be beneficial as you progress through the course.
Show steps
  • Read through the TensorFlow Tutorial
  • Complete the exercises in the TensorFlow Tutorial
Attend TensorFlow Meetups
Attending TensorFlow meetups will allow you to connect with other TensorFlow users and learn from their experiences.
Show steps
  • Find a TensorFlow meetup in your area
  • Attend the meetup and participate in the discussions
Follow TensorFlow Tutorials
Following TensorFlow tutorials will provide you with hands-on experience and help you to apply the concepts you learn in the course to practical problems.
Show steps
  • Find a TensorFlow tutorial that is relevant to your interests or learning goals
  • Follow the steps in the tutorial
  • Experiment with the code and try to understand how it works
Five other activities
Expand to see all activities and additional details
Show all eight activities
Volunteer for a TensorFlow Project
Volunteering for a TensorFlow project will allow you to gain hands-on experience and contribute to the community.
Show steps
  • Find a TensorFlow project that you are interested in
  • Contact the project leader and express your interest in volunteering
TensorFlow Coding Practice
Solving TensorFlow coding problems will help you to develop your skills and improve your understanding of the material.
Show steps
  • Find a TensorFlow coding problem that is challenging but achievable
  • Try to solve the problem on your own
  • If you get stuck, refer to the TensorFlow documentation or online resources for help
Write a TensorFlow Blog Post
Writing a TensorFlow blog post will help you to organize your thoughts and understanding of the material, and it will also allow you to share your knowledge with others.
Show steps
  • Choose a topic for your blog post
  • Research your topic and gather information
  • Write your blog post
Build a TensorFlow Portfolio
Building a TensorFlow portfolio will allow you to showcase your skills and knowledge to potential employers or clients.
Show steps
  • Choose a few TensorFlow projects to include in your portfolio
  • Create a website or online portfolio to showcase your projects
Contribute to TensorFlow
Contributing to TensorFlow will allow you to learn from the experts and help to improve the project.
Show steps
  • Find an issue on the TensorFlow GitHub repository
  • Fix the issue and submit a pull request

Career center

Learners who complete Implementing Predictive Analytics with TensorFlow will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Science methodologies help guide businesses to make decisions that drive optimal outcomes. Data Scientists are professionals with the ability to extract meaningful information from big data sets. This ability is made possible via the use of machine learning and artificial intelligence. Implementing Predictive Analytics with TensorFlow can help you build a foundation in these areas, which will make you an attractive candidate for Data Scientist positions.
Machine Learning Engineer
Machine Learning (ML) Engineers work with data scientists to design, develop, and build ML models. They also work to identify the best ML algorithms for solving specific business problems and to integrate ML models into existing systems. This course can help you build a solid foundation in ML, which will make you a more competitive candidate for Machine Learning Engineer roles.
Data Analyst
Data Analysts play a critical role in transforming raw data into usable insights for businesses. They use their skills in data analysis, statistics, and programming to identify trends, patterns, and anomalies in data. Implementing Predictive Analytics with TensorFlow can help you develop the skills you need to become a successful Data Analyst.
Software Engineer
Software Engineers design, develop, and maintain software applications. Many Software Engineers who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Software Engineers.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions about future events. Many Quantitative Analysts who work in finance and risk management use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Quantitative Analysts.
Research Scientist
Research Scientists conduct research and develop new technologies and products. They use their knowledge of science, engineering, and mathematics to solve complex problems. Many Research Scientists who work in data science and machine learning use TensorFlow in their research. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Research Scientists.
Business Analyst
Business Analysts use data and analysis to solve business problems. Many Business Analysts who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Business Analysts.
Financial Analyst
Financial Analysts evaluate the financial performance of companies and make recommendations to investors. Many Financial Analysts who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Financial Analysts.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve complex business problems. Many Operations Research Analysts who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Operations Research Analysts.
Consultant
Consultants provide advice and guidance to businesses on a variety of topics, including data science and machine learning. Many Consultants who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Consultants.
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. Many Actuaries who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Actuaries.
Risk Manager
Risk Managers identify and assess risks to businesses. Many Risk Managers who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Risk Managers.
Product Manager
Product Managers are responsible for the development and launch of new products and features. Many Product Managers who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Product Managers.
Statistician
Statisticians collect, analyze, and interpret data. Many Statisticians who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Statisticians.
Data Architect
Data Architects design and build data systems that support the needs of businesses. Many Data Architects who work in data science and machine learning use TensorFlow in their work. By taking this course, you can learn the basics of TensorFlow and gain a competitive edge in the job market for Data Architects.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Implementing Predictive Analytics with TensorFlow.
Provides a comprehensive overview of reinforcement learning concepts and algorithms. It valuable resource for anyone who wants to learn more about the fundamentals of reinforcement learning.
Provides a comprehensive overview of deep learning concepts and algorithms, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for anyone who wants to learn more about the fundamentals of deep learning.
Provides a comprehensive overview of data science and machine learning concepts and algorithms, using Python as the programming language. It valuable resource for anyone who wants to learn more about data science and machine learning using Python.
Provides a comprehensive overview of machine learning concepts and algorithms, using Java as the programming language. It valuable resource for anyone who wants to learn more about machine learning using Java.
Provides a collection of recipes for solving common machine learning problems using TensorFlow 2.0. It covers everything from data preprocessing to model evaluation.

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