Measurement system in Mechatronics: Last minute preparation Mechatronics Lectures

Measurement system in Mechatronics : Mechatronics Lectures

Classification of sensors in Mechatronics : Mechatronics Lectures

What is Mechatronics : Last minute preparation Mechatronics Lectures

Deep Learning VM Images

Imagine if you could avoid the headache of setting up new libraries, configuring them, and making sure they are all compatible. In this episode of AI Adventures, Yufeng shows you how to take advantage of deep learning VM images on Google Compute Engine to make setting up new environments a piece of cake.  

How to Import a Keras model into TensorFlow.js

How can we get a Keras model to run on TensorFlow.js? One of the best things about TensorFlow.js is that it has the ability to collaborate across a range of platforms, languages, and devices. In this episode of AI Adventures, Yufeng shows you how to import a Keras model into TensorFlow.js.  

Getting Started with TensorFlow.js

TensorFlow.js is an ecosystem of JavaScript based tools for training and deploying machine learning models. In this episode of AI Adventures, learn all about getting started with Tensorflow.js through tutorials like training a convolutional neural network in your browser and building a Pac-Man game that’s played with data from your webcam! This is only a beginning… stay tuned for deep dives on TensorFlow.js coming soon!  

Scaling up Keras with Estimators (AI Adventures)

When you convert a Keras model to a TensorFlow Estimator, you get the best of both worlds: easy to read Keras model syntax along with distributed training with TensorFlow. In this episode of AI Adventures, Yufeng shows you how to scale up a Keras model with estimators so that it can run larger datasets or across many machines. Plus, it makes it easy to do model serving once the training is complete!  

Getting Started with Keras (AI Adventures)

Getting started with Keras has never been easier! Not only is it built into TensorFlow, but when you combine it with Kaggle Kernels you don’t have to install anything! Plus you get to take advantage of the resources from the Kaggle community. In this episode of AI Adventures, Yufeng shows you how to get started with Keras. Take a look!  

Serving Scikit-learn Models at Scale

Scikit-learn is a great tool for building your models. When it comes time to deploy them to prediction, scale up using Google Cloud ML Engine. In this episode of AI Adventures, Yufeng shows you how to set up your own deployment pipeline with scikit-learn so you can go back to focusing on tuning your model!  

Learning Scikit-Learn (AI Adventures)

Scikit-learn is a well-documented and well-loved Python machine learning library. The library is maintained and reliable, offering a vast collection of machine learning algorithms for you to incorporate into your projects. If you haven’t tried scikit-learn, you definitely should!   In this episode if AI Adventures, Yufeng gives an overview of scikit-learn and shows an example of scikit-learn in a kaggle kernel.  

AutoML Vision – Part 2 (AI Adventures)

In part one of the AI Adventures intro to AutoML Vision, Yufeng talked about what AutoML Vision is used for and showed how to gather and prepare our training data. Stick around for part two where he shows how to use the data to train our model!  

AutoML Vision – Part 1 (AI Adventures)

In this episode of AI Adventures, Yufeng Guo uses AutoML Vision to build and employ a machine learning model that recognizes different types of….chairs! In part 1, he’ll walk you through gathering the data and creating a csv file that describes the location and label for all the images in the dataset. Don’t miss part 2 to see how the model performs!  

How to Make a Data Science Project with Kaggle (AI Adventures)

It can take a lot of tools to do data science, but Kaggle is a one-stop shop that provides all the tools to share and collaborate on data science projects. In the episode of AI Adventures, Yufeng is joined by Megan Risdal, product lead for datasets at Kaggle. They’ll teach you how to make a data science project with Kaggle, and more!  

BigQuery and Open Datasets

We all love data. But it can be hard to make practical use of large datasets. In this episode of AI Adventures, Yufeng Guo introduces BigQuery public datasets, which allow you to query huge datasets with great responsiveness without needing to worry about the storage costs. Time to break out your big data toolbox, because these queries are going to be big!  

AI Adventures: art, science, and tools of machine learning (Google I/O ’18)

Looking to get more insights from your data, but don’t know where to begin? Dive into machine learning and the discovery journey of applying it to your datasets with this session based on the YouTube series “AI Adventures”.  

Quick Draw: the biggest doodle dataset (AI Adventures)

In this episode of AI Adventures, Yufeng explores the massive “Quick, Draw!” dataset, a collection of over 1 billion doodles, drawn by users all over the world!  

Visualize your Data with Facets (AI Adventures)

In this episode of AI Adventures, Yufeng explains how to use Facets, a project from Google Research, to visualize your dataset, find interesting relationships, and clean your data for machine learning.  

TensorFlow Object Detection on iOS (AI Adventures)

In this interview of AI Adventures, Yufeng interviews Developer Advocate Sara Robinson to talk about a custom object detection iOS app she built to detect Taylor Swift. We’ll cover everything from training a model with transfer learning, to serving the model in the cloud, to making prediction requests to the model from an iOS device (in Swift!).  

Print Statements in TensorFlow (AI Adventures)

In this episode of AI Adventures, Yufeng explains how to properly use print statements in your TensorFlow graph.