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Understanding the Foundations of TensorFlow
Janani Ravi
Janani Ravi
This course introduces TensorFlow, an open source data flow library for numerical computations using data flow graphs.
Read more
This course introduces TensorFlow, an open source data flow library for numerical computations using data flow graphs.
Read more
This course introduces TensorFlow, an open source data flow library for numerical computations using data flow graphs.
In this course, Understanding the Foundations of TensorFlow, you'll learn the TensorFlow library from very first principles. First, you'll start with the basics of machine learning using linear regression as an example and focuses on understanding fundamental concepts in TensorFlow. Next, you'll discover how to apply them to machine learning, the concept of a Tensor, the anatomy of a simple program, basic constructs such as constants, variables, placeholders, sessions, and the computation graph. Then, you'll be introduced to TensorBoard, the visualization tool used to view and debug the data flow graphs. You'll work with basic math operations and image transformations to see how common computations are performed. Finally, you'll solve a real world machine learning problem using the MNIST handwritten dataset and the k-nearest-neighbours algorithm. By the end of this course, you'll have a better understanding of the foundations of TensorFlow.
Register for this course and see more details by visiting:
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What's inside
Syllabus
Course Overview
Introducing TensorFlow
Introducing Computation Graphs
Digging Deeper into Fundamentals
Read more
Syllabus
Course Overview
Introducing TensorFlow
Introducing Computation Graphs
Digging Deeper into Fundamentals
Read more
Working with Images
Solving Basic Math Functions
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops foundational concepts in TensorFlow, a fundamental library for data flow computations using data flow graphs
Introduces core machine learning concepts while using TensorFlow, suitable for learners in the early stages of their machine learning journey
Delves into practical applications, including image transformations and solving math functions, enhancing comprehension of TensorFlow's capabilities
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Career center
Learners who complete Understanding the Foundations of TensorFlow will develop knowledge and skills
that may be useful to these careers:
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data and make investment recommendations. This course may be useful as you develop a strong foundation in TensorFlow, which is widely used in the financial industry for applications such as risk management and algorithmic trading.
Research Scientist
Research Scientist
A Research Scientist conducts scientific research to develop new knowledge and technologies. This course may be useful as you explore novel approaches to machine learning and artificial intelligence, and apply your knowledge to real-world problems.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning systems to solve real-world problems. This course may be useful as you build models for supervised and unsupervised learning, and gain hands-on experience with image recognition using TensorFlow.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst collects, analyzes, and interprets data to help businesses improve their performance. This course may be useful as you work with data to identify trends and patterns, and gain experience in using TensorFlow for data visualization and decision-making.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, and interprets data to help businesses make informed decisions. This course may be useful as you work with data in a variety of formats, and gain experience in using TensorFlow for data analysis and visualization.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and statistical models to solve complex business problems. This course may be useful as you develop a strong foundation in TensorFlow, which is used in a variety of operations research applications, such as optimization and simulation.
Financial Analyst
Financial Analyst
A Financial Analyst provides financial advice to individuals and businesses. This course may be useful as you work with financial data and models, and gain experience in using TensorFlow for financial analysis and forecasting.
Risk Analyst
Risk Analyst
A Risk Analyst identifies, assesses, and manages risks for businesses and organizations. This course may be useful as you develop a strong foundation in TensorFlow, which is used in a variety of risk management applications, such as fraud detection and credit scoring.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data to provide insights and make decisions. This course may be useful as you work with data in a variety of formats, and gain experience in using TensorFlow for statistical analysis and modeling.
Actuary
Actuary
An Actuary uses mathematical and statistical models to assess and manage financial risks. This course may be useful as you develop a strong foundation in TensorFlow, which is used in a variety of actuarial applications, such as insurance pricing and risk modeling.
Data Scientist
Data Scientist
A Data Scientist collects, analyzes, and interprets data to extract meaningful insights and solve complex business problems. This course may be useful as you work with TensorBoard, the visualization tool used to view and debug the data flow graphs.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines to support data-driven applications. This course may be useful as you work with data in a variety of formats, and gain experience in using TensorFlow for data processing and transformation.
Software Tester
Software Tester
A Software Tester evaluates software to ensure it meets requirements and performs as expected. This course may be useful as you gain experience in using TensorFlow for testing and debugging machine learning models.
Software Developer
Software Developer
A Software Developer designs, develops, and implements software using a variety of programming languages. This course may be useful as you work on data-driven applications and processes.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. This course may be useful as you gain experience in using TensorFlow for data storage and retrieval.
For more career information including salaries, visit:
OpenCourser.com/course/jenr2g/understanding
Reading list
We've selected ten 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
Understanding the Foundations of TensorFlow.
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A comprehensive textbook on deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks.
A comprehensive guide to TensorFlow, with a focus on deep learning applications.
A practical guide to machine learning using Python, with a focus on popular libraries like scikit-learn, Keras, and TensorFlow.
Save
Provides a comprehensive overview of TensorFlow, covering the basics of neural networks, convolutional neural networks, and recurrent neural networks. It uses a practical, hands-on approach, with plenty of examples and exercises to help readers learn the material.
A practical guide to deep learning using the Keras library, with a focus on building and training deep learning models.
Provides a comprehensive overview of TensorFlow, covering the basics of neural networks, convolutional neural networks, and recurrent neural networks. It uses a practical, hands-on approach, with plenty of examples and exercises to help readers learn the material.
Provides a comprehensive overview of TensorFlow, covering the basics of neural networks, convolutional neural networks, and recurrent neural networks. It uses a practical, hands-on approach, with plenty of examples and exercises to help readers learn the material.
Introduces core machine learning concepts using Python code, with chapters on NumPy, Pandas, scikit-learn, and Tensorflow.
Provides a comprehensive overview of TensorFlow for computer vision. It covers the theoretical foundations of computer vision, as well as practical applications using TensorFlow.
Provides a comprehensive overview of TensorFlow for time series forecasting. It covers the theoretical foundations of time series forecasting, as well as practical applications using TensorFlow.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jenr2g/understanding
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Time
165 hours
Level
Introductory
Via
Pluralsight
Instructor
Janani Ravi
Language
English
This course belongs to a
collection
called
Building Machine Learning Solutions with Tensorflow. It's comprised of 11 courses:
- TensorFlow 1: Getting Started
- Understanding the Foundations of TensorFlow (viewing)
- Building Regression Models Using TensorFlow 1
- Building Classification Models with TensorFlow
- Building Unsupervised Learning Models with TensorFlow
- Debugging and Monitoring TensorFlow Programs
- Deploying TensorFlow Models to AWS, Azure, and the GCP
- Language Modeling with Recurrent Neural Networks in TensorFlow
- Implementing Image Recognition Systems with TensorFlow 1
- Implementing Predictive Analytics with TensorFlow
- Sentiment Analysis with Recurrent Neural Networks in TensorFlow
Good to know
Develops foundational concepts in TensorFlow, a fundamental library for data flow computations using data flow graphs
Introduces core machine learning concepts while using TensorFlow, suitable for learners in the early stages of their machine learning journey
Delves into practical applications, including image transformations and solving math functions, enhancing comprehension of TensorFlow's capabilities
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