The holiday shopping season is a great time to find a robot vacuum at a good sale price, and one of iRobot's most advanced devices is $200 off right now. The Roomba S9 vacuum is down to $900, which is a record low for this model. The "plus" version comes with a Clean Base, but if you can do without that, the regular S9 vacuum is also discounted to $700. Since these remain expensive gadgets, you'll qualify for Wellbots' free shipping and the retailer also offers no sales tax outside New York. These robo-vacs do everything that the well-loved Roomba i7 series does, but they also have a few extra perks.

The DIY spirit is alive and well these days, especially with individuals who have a technical mind. Regardless of age, these people enjoy working on and completing projects -- they just need the resources, tools and a bit of direction to make it happen. If you have a DIYer in your life, you'll want to check out this roundup of six DIY kits that make excellent gifts for the holidays. Circuit Scribe's conductive ink pen, sweet magnetic modules and plain old printer paper allow kids to merge their creativity with science as they build exciting circuits. By placing paper over the steel sheet included in the kit, your child turns the paper into a base for blinking lights, beeping buzzers and whirling motors. Alongside all of the essential materials, this kit comes with an easy-to-follow instructional manual booklet and workbook to guide your children through the process of learning about circuits and switches.

This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications.

Walmart has found a new way to celebrate the holidays in the era of lockdowns and social distancing: high-flying drone shows put on at physical locations and streamed for online viewing. The shows will use almost 1,000 Intel drones to form complex shapes in the night sky, moving in time to Christmas songs like "Frosty the Snowman" by Bing Crosby and "Run Run Rudolph" by Kelly Clarkson. "After a particularly tough year, we want customers and communities to enjoy a moment of rest, peace and hope," said William White, Walmart's chief marketing officer in a press release. "We've been finding ways to help families enjoy seasonal traditions in a year when they thought it might not be possible." Never one to miss a merchandising opportunity, Walmart will also be airing a holiday shortly before the show, "DreamWorks Trolls Holiday."

We are pleased to announce the launch of Python support for Amazon CodeGuru, a service for automated code reviews and application performance recommendations. CodeGuru is powered by program analysis and machine learning, and trained on best practices and hard-learned lessons across millions of code reviews and thousands of applications profiled on open-source projects and internally at Amazon. The launch of Python support extends CodeGuru beyond its original Java support. Python is a widely used language for various use cases, including web app development and DevOps. Python's growth in data analysis and machine learning areas is driven by its rich frameworks and libraries.

Chatbots have become an increasingly important channel for businesses to service their customers. Chatbots provide 24/7 availability and can help customers interact with brands anywhere, anytime and on any device. To effectively utilize chatbots, they must be built with good design, development, test, and deployment practices. This post provides you with a framework that helps you automate the testing processes and reduce the overall bot development cycle for Amazon Lex bots. Amazon Lex is a service for building conversational interfaces into any application using voice and text.

In the past year, lockdowns and other COVID-19 safety measures have made online shopping more popular than ever, but the skyrocketing demand is leaving many retailers struggling to fulfill orders while ensuring the safety of their warehouse employees. Researchers at the University of California, Berkeley, have created new artificial intelligence software that gives robots the speed and skill to grasp and smoothly move objects, making it feasible for them to soon assist humans in warehouse environments. The technology is described in a paper published online today (Wednesday, Nov. 18) in the journal Science Robotics. Automating warehouse tasks can be challenging because many actions that come naturally to humans -- like deciding where and how to pick up different types of objects and then coordinating the shoulder, arm and wrist movements needed to move each object from one location to another -- are actually quite difficult for robots. Robotic motion also tends to be jerky, which can increase the risk of damaging both the products and the robots.

In today's world, being able to quickly bring on-premises machine learning (ML) models to the cloud is an integral part of any cloud migration journey. This post provides a step-by-step guide for launching a solution that facilitates the migration journey for large-scale ML workflows. This solution was developed by the Amazon ML Solutions Lab for customers with streaming data applications (e.g., predictive maintenance, fleet management, autonomous driving). Some of the AWS services used in this solution include Amazon SageMaker, which is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy ML models quickly, and Amazon Kinesis, which helps with real-time data ingestion at scale. Being able to automatically refresh ML models with new data can be of high value to any business when an ML model drifts.

Score savings on these top-rated Amazon picks. Purchases you make through our links may earn us a commission. Black Friday and Cyber Monday went by in a flash, but whether you charged up a storm or didn't get a chance to shop at all, one fact remains the same: There's still plenty of deals to take advantage of right now. If you still have some holiday gifts left to buy, there's one retailer in particular that's sure to help you check them off your list: Amazon. Get expert shopping advice delivered to your phone. Sign up for text message alerts from the deal-hunting nerds at Reviewed.

AWS Glue DataBrew is a new visual data preparation tool that makes it easy for data analysts and data scientists to clean and normalize data to prepare it for analytics and machine learning (ML). In this post, we examine a sample ML use case and show how to use DataBrew and a Jupyter notebook to upload a dataset, clean and normalize the data, and train and publish an ML model. We look for anomalies by applying the Amazon SageMaker Random Cut Forest (RCF) anomaly detection algorithm on a public dataset that records power consumption for more than 300 random households. To make it easier for you to get started, we created an AWS CloudFormation template that automatically configures a Jupyter notebook instance with the required libraries and installs the plugin. We used Amazon Deep Learning AMI to configure the out-of-the-box Jupyter server.