Building Machine Learning Solutions with Tensorflow (Path)

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.
• Build your first TensorFlow project, and create regression, classification, and clustering models.
• Debug and deploy your TensorFlow model.
• Use TensorFlow across an array of high-level cognitive computing problems, such as sentiment analysis, language modeling, image recognition, and predictive analytics.
Courses in this path
A1. TensorFlow. Getting Started (Jerry Kurata, 2017)
A2. Understanding the Foundations of TensorFlow (Janani Ravi, 2017)
A3. Building Regression Models Using TensorFlow (Vitthal Srinivasan, 2017)
A4. Building Classification Models with TensorFlow (Janani Ravi, 2017)
A5. Building Unsupervised Learning Models with TensorFlow (Janani Ravi, 2017)
B1. Debugging and Monitoring TensorFlow Programs (Janani Ravi, 2018)
B2. Deploying TensorFlow Models to AWS, Azure, and the GCP (Janani Ravi, 2018)
C1. Language Modeling with Recurrent Neural Networks in TensorFlow (Janani Ravi, 2018)
C2. Implementing Image Recognition Systems with TensorFlow (Jon Flanders, 2019)
C3. Implementing Predictive Analytics with TensorFlow (Justin Flett, 2018)
C4. Sentiment Analysis with Recurrent Neural Networks in TensorFlow (Janani Ravi, 2017)
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