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Implementing Predictive Analytics with TensorFlow

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

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

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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.

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Read through the TensorFlow Tutorial
Complete the exercises in the TensorFlow Tutorial

Attend TensorFlow Meetups

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Attending TensorFlow meetups will allow you to connect with other TensorFlow users and learn from their experiences.

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Find a TensorFlow meetup in your area
Attend the meetup and participate in the discussions

Follow TensorFlow Tutorials

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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.

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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

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Volunteer for a TensorFlow Project

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Volunteering for a TensorFlow project will allow you to gain hands-on experience and contribute to the community.

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Find a TensorFlow project that you are interested in
Contact the project leader and express your interest in volunteering

TensorFlow Coding Practice

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Solving TensorFlow coding problems will help you to develop your skills and improve your understanding of the material.

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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

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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.

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Choose a topic for your blog post
Research your topic and gather information
Write your blog post

Build a TensorFlow Portfolio

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Building a TensorFlow portfolio will allow you to showcase your skills and knowledge to potential employers or clients.

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Choose a few TensorFlow projects to include in your portfolio
Create a website or online portfolio to showcase your projects

Contribute to TensorFlow

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Contributing to TensorFlow will allow you to learn from the experts and help to improve the project.

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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.

See salaries and explore the career path for Data Scientist

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.

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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.

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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.

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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.

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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.

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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.

See salaries and explore the career path for Business Analyst

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

Reinforcement Learning, second edition

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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.

Reinforcement Learning, second edition: An...

Hardcover

$$$

Reinforcement Learning, second edition: An...

Kindle Edition

$$$

Deep Learning

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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.

Implementing Predictive Analytics with TensorFlow

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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