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MACHINE LEARNING
● Machine learning refers to the use
of algorithms to parse data, process
and learn from it, in order to make
predictions or determinations about
something.
● Machine learning is a field of
computer science that uses
statistical techniques to give
computer systems the ability to
"learn" with data, without being
explicitly programmed.
DEEP LEARNING
● Deep learning is a subfield of
machine learning concerned with
algorithms inspired by the structure
and function of the brain called
artificial neural networks (ANNs)
● Compared to older ML algorithms,
Deep Learning performs better with
a large amount of data
WHAT IS TENSORFLOW...?
● Originally developed by Google
Brain Team within Google's AI
Organization.
● TensorFlow is an open source
software library for high
performance numerical
computation.
● It's flexible architecture allows easy
deployment of computation across
variety of platforms (CPUs, GPUs,
TPUs)
WHAT IS TENSORFLOW...?
● TensorFlow comes with strong support for Machine Learning and Deep
Learning.
● TensorFlow is cross platform and it nearly runs on everything.
● TensorFlow can be used for all machine learning algorithms, but deep
learning is kind of specific to neural networks.
● TensorFlow derives its name from the multidimensional arrays known as
tensors, which are used by the neural networks for different operations.
TENSORFLOW WITH EDUONIX
● While other courses often just brush up on TensorFlow and their basics, they leave
you confused for wanting more. This is why Eduonix have designed a complete
tutorial that shows up the ins and outs of TensorFlow.
● The course also includes the foundation, lifecycle, TensorBoard and much more.
● The course focuses on providing something for every user from newbie to advanced
ones.
● The course contains perfect combination of theory and practical application.
● At the end of this course, you will have the knowledge of TensorFlow and the
experience to actually start working with TensorFlow and even build your very own
projects!
TENSORFLOW WITH EDUONIX CONTD...
What you’ll learn in this course:
● A detailed introduction into TensorFlow
● Familiarity with TensorFlow Foundation
● Machine Learning Lifecycle and TensorBoard
● Logistic Regression & Neural Networks Basics
● Single & Multiple Hidden Layer Neural Networks
● Convolutional Neural Networks
● Deep Learning
● And so much more!
Eduonix Introduces
TensorFlow for Beginners @ $15
To Get this Course at $15 Use Coupon Code : DISCOUNT15
● Lectures: 19
● Video: 04 hours
● Language: English
● Includes: 30 day money back
guarantee!
Certificate of
Completion.
Lifetime Access.
Reference Link : https://goo.gl/CRLBYw
TABLE OF CONTENTS
● SECTION 1 : Introduction
● SECTION 2 : TensorFlow Foundations
● SECTION 3 : ML Lifecycle & TensorBoard
● SECTION 4 : The Machine Learning Lifecycle & Using TensorBoard
● SECTION 5 : Logistic Regression & NN Basic
● SECTION 6 : Single & Multiple Hidden Layer Nns
● SECTION 7 : Convolutional NNs
● SECTION 8 : Deep Learning
● SECTION 9 : Final Project
Connect with us on Social Platform
Thank You!!!

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Tensorflow for Beginners

  • 1.
  • 2. MACHINE LEARNING ● Machine learning refers to the use of algorithms to parse data, process and learn from it, in order to make predictions or determinations about something. ● Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" with data, without being explicitly programmed.
  • 3. DEEP LEARNING ● Deep learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks (ANNs) ● Compared to older ML algorithms, Deep Learning performs better with a large amount of data
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  • 5. WHAT IS TENSORFLOW...? ● Originally developed by Google Brain Team within Google's AI Organization. ● TensorFlow is an open source software library for high performance numerical computation. ● It's flexible architecture allows easy deployment of computation across variety of platforms (CPUs, GPUs, TPUs)
  • 6. WHAT IS TENSORFLOW...? ● TensorFlow comes with strong support for Machine Learning and Deep Learning. ● TensorFlow is cross platform and it nearly runs on everything. ● TensorFlow can be used for all machine learning algorithms, but deep learning is kind of specific to neural networks. ● TensorFlow derives its name from the multidimensional arrays known as tensors, which are used by the neural networks for different operations.
  • 7. TENSORFLOW WITH EDUONIX ● While other courses often just brush up on TensorFlow and their basics, they leave you confused for wanting more. This is why Eduonix have designed a complete tutorial that shows up the ins and outs of TensorFlow. ● The course also includes the foundation, lifecycle, TensorBoard and much more. ● The course focuses on providing something for every user from newbie to advanced ones. ● The course contains perfect combination of theory and practical application. ● At the end of this course, you will have the knowledge of TensorFlow and the experience to actually start working with TensorFlow and even build your very own projects!
  • 8. TENSORFLOW WITH EDUONIX CONTD... What you’ll learn in this course: ● A detailed introduction into TensorFlow ● Familiarity with TensorFlow Foundation ● Machine Learning Lifecycle and TensorBoard ● Logistic Regression & Neural Networks Basics ● Single & Multiple Hidden Layer Neural Networks ● Convolutional Neural Networks ● Deep Learning ● And so much more!
  • 9. Eduonix Introduces TensorFlow for Beginners @ $15 To Get this Course at $15 Use Coupon Code : DISCOUNT15 ● Lectures: 19 ● Video: 04 hours ● Language: English ● Includes: 30 day money back guarantee! Certificate of Completion. Lifetime Access. Reference Link : https://goo.gl/CRLBYw
  • 10. TABLE OF CONTENTS ● SECTION 1 : Introduction ● SECTION 2 : TensorFlow Foundations ● SECTION 3 : ML Lifecycle & TensorBoard ● SECTION 4 : The Machine Learning Lifecycle & Using TensorBoard ● SECTION 5 : Logistic Regression & NN Basic ● SECTION 6 : Single & Multiple Hidden Layer Nns ● SECTION 7 : Convolutional NNs ● SECTION 8 : Deep Learning ● SECTION 9 : Final Project
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