We, at Analytics Vidhya, are covering these developments, along with all other major stories in the ML world on AVBytes! We provide links to official research papers so you can deep dive into the theory behind the technology. We also provide links to the source code on GitHub so you can replicate it (and even improve it!) on your own machine.
In the past week, we saw the big names grabbing the headlines – Amazon unveiled the technology behind it’s AWS SageMaker, IBM developed a library that ran the same model on the same data 46 times faster than TensorFlow, Baidu open sourced it’s massive self-driving dataset, SAS developed a ML model to rank the best places to live, etc.
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Below is a round-up of all the happenings in the last week. Click on each title to read the full article.
- IBM’s Machine Learning Library is 46 Times Faster than TensorFlow!: IBM’s new library has blown TensorFlow out of the water! Running a logistic regression model on the same dataset (4.2 million training examples and 1 million variables), they achieved similar results but 46 times quicker than TensorFlow! Read more about this library and get the link to the official research paper inside.
- Baidu has Released a Gigantic Self-Driving Dataset named ApolloScape: Thanks to Baidu, you can design your own self-driving car! They have released an open source dataset that you can access and play around with on your own machines.
- Amazon Unveils the Technology Behind the AWS SageMaker: Want to build ML models without having to worry about limited computation recources? Amazon’s SageMaker is the answer! Yesterday, the company has also unveiled the technology that powers SageMaker. Read all about it here.
- IBM Launches Deep Learning as a Service for ML and AI Developers: Want to build a neural network but don’t have the deep expertise for it? IBM has launched it’s Deep Learning as a Service platform for ML and AI developers that takes the difficulty out of deep learning models!
- SAS’s Machine Learning Model Ranks the Best Places to Live in the World: SAS has developed an algorithm that used over 5 million data points and 8 key variables to rank the best place to live in the world. Details of their approach in this article.
- Google is Using Deep Learning to Make Computers Better with Age!: Our devices slow down and wear out as they age, it can’t be helped. Or can it? Google might have a solution! Using deep learning, they’re aiming to make our machines actually improve with age! Check out the details + the official research paper link inside.
The above AVBytes were published from 19th to 25th March, 2018.
This week was full of exciting developments. We can’t wait to use Baidu’s massive dataset and are eagerly anticipating more details from IBM about their Snap ML library. What excited you the most in the ML world in the past week? Let us know in the comments below.
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