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IBM - Deep Learningwith Tensorflow 

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  • Private Institute

Deep Learningwith Tensorflow
 at 
edX 
Overview

Upskilling is a better roadmap to success. Enroll in this course to learn critical principles of Machine Learning through real-life case studies & examples

Duration

29 hours

Total fee

Free

Mode of learning

Online

Schedule type

Self paced

Difficulty level

Intermediate

Official Website

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Credential

Certificate

Deep Learningwith Tensorflow
Table of content
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  • Overview
  • Highlights
  • Course Details
  • Curriculum
  • Entry Requirements
  • + 1 more item

Deep Learningwith Tensorflow
 at 
edX 
Highlights

  • Earn a certificate of learning on course completion
  • Add a Verified Certificate for ? 7,568
  • This course is offered by IBM
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Deep Learningwith Tensorflow
 at 
edX 
Course details

Who should do this course?
  • This course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises. If you are an aspiring Data Scientist, this course is NOT for you as you need real world expertise to benefit from the content of these courses.
What are the course deliverables?
  • Discuss common regression, classification, and multilabel classification metrics
  • Explain the use of linear and logistic regression in supervised learning applications
  • Describe common strategies for grid searching and cross-validation
  • Employ evaluation metrics to select models for production use
  • Explain the use of tree-based algorithms in supervised learning applications
  • Explain the use of Neural Networks in supervised learning applications
  • Discuss the major variants of neural networks and recent advances
  • Create a neural net model in Tensorflow
  • Create and test an instance of Watson Visual Recognition
  • Create and test an instance of Watson NLU
More about this course
  • Traditional neural networks rely on shallow nets, composed of one input, one hidden layer and one output layer. Deep-learning networks are distinguished from these ordinary neural networks having more hidden layers, or so-called more depth. These kind of nets are capable of discovering hidden structures withinunlabeled and unstructured data (i.e. images, sound, and text), which consitutes the vast majority of data in the world
  • TensorFlow is one of the best libraries to implement deep learning. TensorFlow is a software library for numerical computation of mathematical expressional, using data flow graphs. Nodes in the graph represent mathematical operations, while the edges represent the multidimensional data arrays (tensors) that flow between them. It was created by Google and tailored for Machine Learning. In fact, it is being widely used to develop solutions with Deep Learning.
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Deep Learningwith Tensorflow
 at 
edX 
Curriculum

Model Evaluation and Performance Metrics

Building Machine Learning and Deep Learning Models

Deep Learningwith Tensorflow
 at 
edX 
Entry Requirements

Eligibility criteriaUp Arrow Icon
Conditional OfferUp Arrow Icon
  • Not mentioned

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Deep Learningwith Tensorflow
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Students Ratings & Reviews

4.5/5
Verified Icon4 Ratings
P
Prashant Kumar Prasad
Deep Learningwith Tensorflow
Offered by edX
5
Learning Experience: It was fun and easy learning at edx. I wanted to learn about Tensorflow and CNN in depth. This course definitely helped me in getting that knowledge.
Faculty: The faculty was good and used easy language to make to learning understand easily It was easy to understand and apply industry based curriculum. You get to apply what you learn
Course Support: No
Reviewed on 13 Aug 2022Read More
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M
Mohammad Rafaq
Deep Learningwith Tensorflow
Offered by edX
5
Other: Great course to learn about regression techniques and pipelines. Course structure and faculty- good.
Reviewed on 13 Oct 2020Read More
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Deep Learningwith Tensorflow
 at 
edX 

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