Our Courses

Getting Started with Tensorflow.js

Getting Started with Tensorflow.js

By the end of this project, you will learn how to code a smart webcam to detect people and other everyday objects using a pre-trained COCO-SSD image recognition model with Tensorflow.

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  • 2 hours
  • English
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Using Tensorflow for Image Style Transfer

Using Tensorflow for Image Style Transfer

Have you ever wished you could paint like Van Gogh, Monet or even Picasso? Better yet, have you wished for an easy way to convert your own images into new ones incorporating the style of these famous artists? With Neural Style Transfer, Convolutional Neural Networks (CNNs) distill the essence of the style of any famous artist it is fed, and are able to transfer that style to any other image.

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  • 4 hours
  • English
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Custom and Distributed Training with TensorFlow

Custom and Distributed Training with TensorFlow

In this course, you will: • Learn about Tensor objects, the fundamental building blocks of TensorFlow, understand the difference between the eager and graph modes in TensorFlow, and learn how to use a TensorFlow tool to calculate gradients. • Build your own custom training loops using GradientTape and TensorFlow Datasets to gain more flexibility and visibility with your model training.

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  • 25 hours
  • English
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Implementing Canary Releases of TensorFlow Model Deployments with Kubernetes and Anthos Service Mesh

Implementing Canary Releases of TensorFlow Model Deployments with Kubernetes and Anthos Service Mesh

This is a self-paced lab that takes place in the Google Cloud console. AutoML Vision helps developers with limited ML expertise train high quality image recognition models. In this hands-on lab, you will learn how to train a custom model to recognize different types of clouds (cumulus, cumulonimbus, etc.).

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  • 2 hours
  • English
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Introduction to Computer Vision with TensorFlow

Introduction to Computer Vision with TensorFlow

This is a self-paced lab that takes place in the Google Cloud console. In this lab you create a computer vision model that can recognize items of clothing and then explore what affects the training model.

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  • 1 hour
  • English
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Encoder-Decoder Architecture - Português Brasileiro

Encoder-Decoder Architecture - Português Brasileiro

Este curso apresenta um resumo da arquitetura de codificador-decodificador, que é uma arquitetura de machine learning avançada e frequentemente usada para tarefas sequência para sequência (como tradução automática, resumo de textos e respostas a perguntas). Você vai conhecer os principais componentes da arquitetura de codificador-decodificador e aprender a treinar e disponibilizar esses modelos. No tutorial do laboratório relacionado, você vai codificar uma implementação simples da arquitetura de codificador-decodificador para geração de poesia desde a etapa inicial no TensorFlow.

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  • English
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Cifar-10 Image Classification with Keras and Tensorflow 2.0

Cifar-10 Image Classification with Keras and Tensorflow 2.0

In this guided project, we will build, train, and test a deep neural network model to classify low-resolution images containing airplanes, cars, birds, cats, ships, and trucks in Keras and Tensorflow 2.

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  • 2 hours
  • English
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Machine Learning Data Lifecycle in Production

Machine Learning Data Lifecycle in Production

**Starting May 8, enrollment for the Machine Learning Engineering for Production Specialization will be closed.

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  • 22 hours
  • English
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Transfer Learning for NLP with TensorFlow Hub

Transfer Learning for NLP with TensorFlow Hub

This is a hands-on project on transfer learning for natural language processing with TensorFlow and TF Hub.

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  • 2 hours
  • English
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Deep Learning for Business

Deep Learning for Business

Your smartphone, smartwatch, and automobile (if it is a newer model) have AI (Artificial Intelligence) inside serving you every day. In the near future, more advanced “self-learning” capable DL (Deep Learning) and ML (Machine Learning) technology will be used in almost every aspect of your business and industry. So now is the right time to learn what DL and ML is and how to use it in advantage of your company.

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  • 8 hours
  • English
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Detect Fake News in Python with Tensorflow

Detect Fake News in Python with Tensorflow

"Fake News" is a word used to mean different things to different people.

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  • 2 hours
  • English
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Practical Python for AI Coding 1

Practical Python for AI Coding 1

Introduction video: https://youtu.be/TRhwIHvehR0 This course is for a complete novice of Python coding, so no prior knowledge or experience in software coding is required. This course selects, introduces, and explains Python syntaxes, functions, and libraries that were frequently used in AI coding. In addition, this course introduces vital syntaxes, and functions often used in AI coding and explains the complementary relationship among NumPy, Pandas, and TensorFlow, so this course is helpful for even seasoned python users.

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  • 11 hours
  • English
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TensorFlow for Beginners: Basic Binary Image Classification

TensorFlow for Beginners: Basic Binary Image Classification

The goal of this project is to introduce beginners to the basic concepts of machine learning using TensorFlow. The project will include, how to set up the tool and get started as well as understanding the fundamentals of machine learning/neural network model and its key concepts. Learning how to use TensorFlow for implementing machine learning algorithms, data preprocessing, supervised learning. Additionally, learners develop skills in evaluating and deploying machine learning models using TensorFlow.

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  • 4 hours
  • English
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Image Noise Reduction with Auto-encoders using TensorFlow

Image Noise Reduction with Auto-encoders using TensorFlow

In this 2-hour long project-based course, you will learn the basics of image noise reduction with auto-encoders.

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  • 3 hours
  • English
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Deep Learning with Tensorflow

Deep Learning with Tensorflow

Much of theworld's data is unstructured. Think images, sound, and textual data. Learn how to apply Deep Learning with TensorFlow to this type of data to solve real-world problems.

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Using Machine Learning in Trading and Finance

Using Machine Learning in Trading and Finance

This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading.

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  • 19 hours
  • English
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Create a Superhero Name Generator with TensorFlow

Create a Superhero Name Generator with TensorFlow

In this guided project, we are going to create a neural network and train it on a small dataset of superhero names to learn to generate similar names. The dataset has over 9000 names of superheroes, supervillains and other fictional characters from a number of different comic books, TV shows and movies. Text generation is a common natural language processing task. We will create a character level language model that will predict the next character for a given input sequence.

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  • 3 hours
  • English
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Identify Horses or Humans with TensorFlow and Vertex AI

Identify Horses or Humans with TensorFlow and Vertex AI

This is a self-paced lab that takes place in the Google Cloud console. In this lab, you use convolutions to recognize features in an image where the subject can be anywhere in the image!

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  • 2 hours
  • English
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Using TensorFlow with Amazon Sagemaker

Using TensorFlow with Amazon Sagemaker

Please note: You will need an AWS account to complete this course.

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  • 3 hours
  • English
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Feature Engineering - 한국어

Feature Engineering - 한국어

이 과정에서는 Vertex AI Feature Store 사용의 이점, ML 모델의 정확성을 개선하는 방법, 가장 유용한 특성을 만드는 데이터 열을 찾는 방법을 살펴봅니다. 이 과정에는 BigQuery ML, Keras, TensorFlow를 사용한 특성 추출에 관한 콘텐츠와 실습도 포함되어 있습니다.

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  • English
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Predicting House Prices with Regression using TensorFlow

Predicting House Prices with Regression using TensorFlow

In this 2-hour long project-based course, you will learn the basics of using Keras with TensorFlow as its backend and you will learn to use it to solve a basic regression problem.

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  • 2 hours
  • English
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Tweet Emotion Recognition with TensorFlow

Tweet Emotion Recognition with TensorFlow

In this 2-hour long guided project, we are going to create a recurrent neural network and train it on a tweet emotion dataset to learn to recognize emotions in tweets. The dataset has thousands of tweets each classified in one of 6 emotions. This is a multi class classification problem in the natural language processing domain. We will be using TensorFlow as our machine learning framework. You will need prior programming experience in Python.

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  • 3 hours
  • English
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Encoder-Decoder Architecture - Español

Encoder-Decoder Architecture - Español

En este curso, se brinda un resumen de la arquitectura de codificador-decodificador, una arquitectura de aprendizaje automático importante y potente para realizar tareas de secuencia por secuencia, como las de traducción automática, resúmenes de texto y respuestas a preguntas. Aprenderás sobre los componentes principales de la arquitectura de codificador-decodificador y cómo entrenar y entregar estos modelos. En la explicación del lab, programarás una implementación sencilla de la arquitectura de codificador-decodificador en TensorFlow para generar poemas desde un comienzo.

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  • English
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Object Localization with TensorFlow

Object Localization with TensorFlow

Welcome to this 2 hour long guided project on creating and training an Object Localization model with TensorFlow. In this guided project, we are going to use TensorFlow's Keras API to create a convolutional neural network which will be trained to classify as well as localize emojis in images. Localization, in this context, means the position of the emojis in the images. This means that the network will have one input and two outputs. Think of this task as a simpler version of Object Detection.

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  • 3 hours
  • English
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Build a Deep Learning Based Image Classifier with R

Build a Deep Learning Based Image Classifier with R

In this 45-min guided project, you will learn the basics of using the Keras interface to R with Tensorflow as its backend to solve an image classification problem.

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  • 3 hours
  • English
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