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EITC/AI/TFF TensorFlow Fundamentals

by admin / Saturday, 06 February 2021 / Published in Uncategorized
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EITC/AI/TFF TensorFlow Fundamentals is the European IT Certification programme on the Google TensorFlow machine learning library enabling programming of artificial intelligence.

The curriculum of the EITC/AI/TFF TensorFlow Fundamentals focuses on the theoretical aspects and practical skills in using TensorFlow library organized within the following structure, encompassing comprehensive video didactic content as a reference for this EITC Certification.

TensorFlow is a free and open-source software library for machine learning. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. It is a symbolic math library based on dataflow and differentiable programming. It is used for both research and production at Google.

TensorFlow was developed by the Google Brain team for internal Google use. It was released under the Apache License 2.0 in 2015.

Starting in 2011, Google Brain built DistBelief as a proprietary machine learning system based on deep learning neural networks. Its use grew rapidly across diverse Alphabet companies in both research and commercial applications. Google assigned multiple computer scientists, including Jeff Dean, to simplify and refactor the codebase of DistBelief into a faster, more robust application-grade library, which became TensorFlow. In 2009, the team, led by Geoffrey Hinton, had implemented generalized backpropagation and other improvements which allowed generation of neural networks with substantially higher accuracy, for instance a 25% reduction in errors in speech recognition.

TensorFlow is Google Brain’s second-generation system. Version 1.0.0 was released on February 11, 2017. While the reference implementation runs on single devices, TensorFlow can run on multiple CPUs and GPUs (with optional CUDA and SYCL extensions for general-purpose computing on graphics processing units). TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. Its flexible architecture allows for the easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. TensorFlow computations are expressed as stateful dataflow graphs. The name TensorFlow derives from the operations that such neural networks perform on multidimensional data arrays, which are referred to as tensors. During the Google I/O Conference in June 2016, Jeff Dean stated that 1,500 repositories on GitHub mentioned TensorFlow, of which only 5 were from Google. In December 2017, developers from Google, Cisco, RedHat, CoreOS, and CaiCloud introduced Kubeflow at a conference. Kubeflow allows operation and deployment of TensorFlow on Kubernetes. In March 2018, Google announced TensorFlow.js version 1.0 for machine learning in JavaScript. In Jan 2019, Google announced TensorFlow 2.0. It became officially available in Sep 2019. In May 2019, Google announced TensorFlow Graphics for deep learning in computer graphics.

To acquaint yourself in-detail with the certification curriculum you can expand and analyze the table below.

The EITC/AI/TFF TensorFlow Fundamentals Certification Curriculum references open-access didactic materials in a video form. Learning process is divided into a step-by-step structure (programmes -> lessons -> topics) covering relevant curriculum parts. Unlimited consultancy with domain experts are also provided.
For details on the Certification procedure check How it Works.

Curriculum Reference Resources

Google TensorFlow
https://www.tensorflow.org/

Google TensorFlow Learning Resources
https://www.tensorflow.org/learn/

TensorFlow API Documentation
https://www.tensorflow.org/api_docs/

TensorFlow Models and Datasets
https://www.tensorflow.org/resources/models-datasets/

TensorFlow Community
https://www.tensorflow.org/community/

Google Cloud AI Platform Training with TensorFlow
https://cloud.google.com/ai-platform/training/docs/tensorflow-2/

Certification Programme Curriculum

Expand All
Introduction to TensorFlow 4 Topics
Expand
Lesson Content
0% Complete 0/4 Steps
Fundamentals of machine learning
Basic computer vision with ML
Introducing convolutional neural networks
Building an image classifier
Neural Structured Learning with TensorFlow 4 Topics
Expand
Lesson Content
0% Complete 0/4 Steps
Neural Structured Learning framework overview
Training with natural graphs
Training with synthesized graphs
Adversarial learning for image classification
Natural Language Processing with TensorFlow 6 Topics
Expand
Lesson Content
0% Complete 0/6 Steps
Tokenization
Sequencing – turning sentences into data
Training a model to recognize sentiment in text
ML with recurrent neural networks
Long short-term memory for NLP
Training AI to create poetry
Programming TensorFlow 4 Topics
Expand
Lesson Content
0% Complete 0/4 Steps
Introduction to TensorFlow coding
Introducing TensorFlow Lite
TensorFlow Lite for Android
TensorFlow Lite for iOS
TensorFlow.js 4 Topics
Expand
Lesson Content
0% Complete 0/4 Steps
TensorFlow.js in your browser
Preparing dataset for machine learning
Building a neural network to perform classification
Using TensorFlow to classify clothing images
Text classification with TensorFlow 2 Topics
Expand
Lesson Content
0% Complete 0/2 Steps
Preparing data for machine learning
Designing a neural network
Overfitting and underfitting problems 2 Topics
Expand
Lesson Content
0% Complete 0/2 Steps
Solving model’s overfitting and underfitting problems – part 1
Solving model’s overfitting and underfitting problems – part 2
Advancing in TensorFlow 2 Topics
Expand
Lesson Content
0% Complete 0/2 Steps
Saving and loading models
TensorFlow Lite, experimental GPU delegate
TensorFlow in Google Colaboratory 6 Topics
Expand
Lesson Content
0% Complete 0/6 Steps
Getting started with Google Colaboratory
Getting started with TensorFlow in Google Colaboratory
Building a deep neural network with TensorFlow in Colab
How to take advantage of GPUs and TPUs for your ML project
Upgrade your existing code for TensorFlow 2.0
Using TensorFlow to solve regression problems
TensorFlow 2.0 1 Topic
Expand
Lesson Content
0% Complete 0/1 Steps
Introduction to TensorFlow 2.0
TensorFlow high-level APIs 3 Topics
Expand
Lesson Content
0% Complete 0/3 Steps
Loading data
Going deep on data and features
Building and refining your models
TensorFlow Extended (TFX) 6 Topics
Expand
Lesson Content
0% Complete 0/6 Steps
ML engineering for production ML deployments with TFX
What exactly is TFX
TFX pipelines
Metadata
Distributed processing and components
Model understanding and business reality
TensorFlow Applications 16 Topics
Expand
Lesson Content
0% Complete 0/16 Steps
Air Cognizer predicting air quality with ML
Helping Doctors Without Borders staff prescribe antibiotics for infections
Helping doctors detect respiratory diseases using machine learning
Utilizing deep learning to predict extreme weather
Helping paleographers transcribe medieval text with ML
Airbnb using ML categorize its listing photos
Using machine learning to tackle crop disease
AI helping to predict floods
Positive current
Daniel and the sea of sound
Beneath the canopy
Using machine learning to predict wildfires
Tracking asteroids with machine learning
Identifying potholes on Los Angeles roads with ML
Dance Like, an app that helps users learn how to dance using machine learning
How machine learning is being used to help save the world’s bees
EITC/AI/TFF TensorFlow Fundamentals
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Programme Home Expand All
Introduction to TensorFlow
4 Topics
Fundamentals of machine learning
Basic computer vision with ML
Introducing convolutional neural networks
Building an image classifier
Neural Structured Learning with TensorFlow
4 Topics
Neural Structured Learning framework overview
Training with natural graphs
Training with synthesized graphs
Adversarial learning for image classification
Natural Language Processing with TensorFlow
6 Topics
Tokenization
Sequencing – turning sentences into data
Training a model to recognize sentiment in text
ML with recurrent neural networks
Long short-term memory for NLP
Training AI to create poetry
Programming TensorFlow
4 Topics
Introduction to TensorFlow coding
Introducing TensorFlow Lite
TensorFlow Lite for Android
TensorFlow Lite for iOS
TensorFlow.js
4 Topics
TensorFlow.js in your browser
Preparing dataset for machine learning
Building a neural network to perform classification
Using TensorFlow to classify clothing images
Text classification with TensorFlow
2 Topics
Preparing data for machine learning
Designing a neural network
Overfitting and underfitting problems
2 Topics
Solving model’s overfitting and underfitting problems – part 1
Solving model’s overfitting and underfitting problems – part 2
Advancing in TensorFlow
2 Topics
Saving and loading models
TensorFlow Lite, experimental GPU delegate
TensorFlow in Google Colaboratory
6 Topics
Getting started with Google Colaboratory
Getting started with TensorFlow in Google Colaboratory
Building a deep neural network with TensorFlow in Colab
How to take advantage of GPUs and TPUs for your ML project
Upgrade your existing code for TensorFlow 2.0
Using TensorFlow to solve regression problems
TensorFlow 2.0
1 Topic
Introduction to TensorFlow 2.0
TensorFlow high-level APIs
3 Topics
Loading data
Going deep on data and features
Building and refining your models
TensorFlow Extended (TFX)
6 Topics
ML engineering for production ML deployments with TFX
What exactly is TFX
TFX pipelines
Metadata
Distributed processing and components
Model understanding and business reality
TensorFlow Applications
16 Topics
Air Cognizer predicting air quality with ML
Helping Doctors Without Borders staff prescribe antibiotics for infections
Helping doctors detect respiratory diseases using machine learning
Utilizing deep learning to predict extreme weather
Helping paleographers transcribe medieval text with ML
Airbnb using ML categorize its listing photos
Using machine learning to tackle crop disease
AI helping to predict floods
Positive current
Daniel and the sea of sound
Beneath the canopy
Using machine learning to predict wildfires
Tracking asteroids with machine learning
Identifying potholes on Los Angeles roads with ML
Dance Like, an app that helps users learn how to dance using machine learning
How machine learning is being used to help save the world’s bees
EITC/AI/TFF TensorFlow Fundamentals

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