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Building Machine Learning Solutions with Tensorflow

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TensorFlow is an open-source machine learning software library developed Google. Since it was released in 2015, it has become one of the most widely-used machine learning libraries. This skill will teach you how to implement the machine learning workflow using TensorFlow, and apply the library from Python to solve simple and complex machine learning problems.

What You'll Learn

  • Design and implementation of machine learning solutions using TensorFlow with Python
  • Applying Tensorflow to common analytical problems, such as classification, clustering, and regression
  • Debugging Tensorflow projects
  • Deploying Tensorflow projects to the cloud
  • Applying Tensorflow to more advanced problems spaces, such as image recognition, language modeling, and predictive analytics.
  • From Pluralsight
    Hours 28
    Instructors Jerry Kurata, J, e, r, y, Janani Ravi, a, n, i, Vitthal Srinivasan, v, t, h, l, Jon Flanders, o, Justin Flett, u, S
    Language English
    Subjects Programming Data Science IT & Networking

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    Courses in this Paths

    Listed in the order in which they should be taken

    Starts Course Information

    On Demand

    TensorFlow: Getting Started

    Developing sophisticated machine learning solutions is a difficult task. There are many processing steps that must be performed, and how this processing is performed is a function...

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    Understanding the Foundations of TensorFlow

    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...

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    Building Regression Models Using TensorFlow

    TensorFlow is all about building neural networks that can "learn" functions, and linear regression can be learnt by the simplest possible neural network - of just 1 neuron! In...

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    Building Classification Models with TensorFlow

    TensorFlow is a great way to implement powerful classification models such as Convolutional Neural Networks and Recurrent Neural Networks. In this course, Building Classification...

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    Building Unsupervised Learning Models with TensorFlow

    Unsupervised learning techniques are powerful, but under utilized and often not well understood. In this course, Building Unsupervised Learning Models with TensorFlow, you'll...

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    Debugging and Monitoring TensorFlow Programs

    An important facet of building good ML models is the ability to debug TensorFlow code when your models do not converge. Traditional debuggers fall short in this regard which is...

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    Deploying TensorFlow Models to AWS, Azure, and the GCP

    Deploying and hosting your trained TensorFlow model locally or on your cloud platform of choice - Azure, AWS or, the GCP, can be challenging. In this course, Deploying TensorFlow...

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    Language Modeling with Recurrent Neural Networks in TensorFlow

    Recurrent Neural Networks (RNN) performance and predictive abilities can be improved by using long memory cells such as the LSTM and the GRU cell. In this course, Language...

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    Implementing Image Recognition Systems with TensorFlow

    Running images through deep learning models is potentially the most typical scenario in which deep learning is used today. In this course, Implementing Image Recognition Systems...

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    Implementing Predictive Analytics with TensorFlow

    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,...

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    Sentiment Analysis with Recurrent Neural Networks in TensorFlow

    Sentiment analysis and natural language processing are common problems to solve using machine learning techniques. Having accurate and good answers to questions without trudging...

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    Pluralsight

    From Pluralsight
    Hours 28
    Instructors Jerry Kurata, J, e, r, y, Janani Ravi, a, n, i, Vitthal Srinivasan, v, t, h, l, Jon Flanders, o, Justin Flett, u, S
    Language English
    Subjects Programming Data Science IT & Networking

    Careers

    An overview of related careers and their average salaries in the US. Bars indicate income percentile (33rd - 99th).

    Research Scientist-Machine Learning $55k

    Cloud Architect - Azure / Machine Learning $75k

    Watson Machine Learning Engineer $81k

    Machine Learning Software Developer $103k

    Software Engineer (Machine Learning) $116k

    Applied Scientist, Machine Learning $130k

    Autonomy and Machine Learning Solutions Architect $131k

    Applied Scientist - Machine Learning -... $136k

    RESEARCH SCIENTIST (MACHINE LEARNING) $147k

    Machine Learning Engineer 2 $161k

    Machine Learning Scientist Manager $170k

    Machine Learning Scientist, Personalization $213k

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    Sorted by relevance