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Our Courses
Advanced Deployment Scenarios with TensorFlow
Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model. In this final course, you’ll explore four different scenarios you’ll encounter when deploying models. You’ll be introduced to TensorFlow Serving, a technology that lets you do inference over the web. You’ll move on to TensorFlow Hub, a repository of models that you can use for transfer learning.
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Course by
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Self Paced
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13 hours
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English
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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Course by
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Self Paced
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3 hours
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English
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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Course by
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Self Paced
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2 hours
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English
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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Course by
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Self Paced
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19 hours
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English
Detect Fake News in Python with Tensorflow
"Fake News" is a word used to mean different things to different people.
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Course by
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Self Paced
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2 hours
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English
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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Course by
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Self Paced
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25 hours
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English
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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Course by
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Self Paced
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4 hours
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English
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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Course by
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Self Paced
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3 hours
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English
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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Course by
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Self Paced
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2 hours
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English
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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Course by
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Self Paced
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English
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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Course by
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Self Paced
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English
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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Course by
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Self Paced
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2 hours
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English
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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Course by
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Self Paced
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4 hours
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English
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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Course by
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Self Paced
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11 hours
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English
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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Course by
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English
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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Course by
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Self Paced
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22 hours
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English
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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Course by
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Self Paced
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2 hours
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English
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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Course by
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Self Paced
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2 hours
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English
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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Course by
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Self Paced
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1 hour
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English
Build and Operate Machine Learning Solutions with Azure
Azure Machine Learning is a cloud platform for training, deploying, managing, and monitoring machine learning models. In this course, you will learn how to use the Azure Machine Learning Python SDK to create and manage enterprise-ready ML solutions. This is the third course in a five-course program that prepares you to take the DP-100: Designing and Implementing a Data Science Solution on Azurecertification exam. The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at a cloud-scale using Azure Machine Learning.
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Course by
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Self Paced
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32 hours
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English
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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Course by
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Self Paced
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8 hours
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English
Using TensorFlow with Amazon Sagemaker
Please note: You will need an AWS account to complete this course.
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Course by
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3 hours
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English
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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Course by
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Self Paced
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3 hours
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English
Fine-tuning Convolutional Networks to Classify Dog Breeds
In this 2 hour-long project, you will learn how to approach an image classification task using TensorFlow.
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Course by
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Self Paced
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3 hours
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English
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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Course by
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Self Paced
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3 hours
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English