The Rise of the Machine Learning Engineer

The evolution of Big Data into machine learning applications ushered in an exciting era of new roles and skillsets that became necessary to implement these technologies. With the Machine Learning Engineer being such a crucial component today, where the evolution of this field will take us tomorrow should be fascinating.

Originally from KDnuggets https://ift.tt/3pWALzJ

source https://365datascience.weebly.com/the-best-data-science-blog-2020/the-rise-of-the-machine-learning-engineer

Computer Vision at Scale With Dask And PyTorch

A tutorial on conducting image classification inference using the Resnet50 deep learning model at scale with using GPU clusters on Saturn Cloud. The results were: 40x faster computer vision that made a 3+ hour PyTorch model run in just 5 minutes.

Originally from KDnuggets https://ift.tt/3fu5VcX

source https://365datascience.weebly.com/the-best-data-science-blog-2020/computer-vision-at-scale-with-dask-and-pytorch

How Machine Learning Works for Social Good

We often discuss applying data science and machine learning techniques in term so of how they help your organization or business goals. But, these algorithms aren’t limited to only increasing the bottom line. Developing new applications that leverage the predictive power of AI to benefit society and those communities in need is an equally valuable endeavor for Data Scientists that will further expand the positive impact of machine learning to the world.

Originally from KDnuggets https://ift.tt/3pOugim

source https://365datascience.weebly.com/the-best-data-science-blog-2020/how-machine-learning-works-for-social-good

Computer Vision Projects with Python

source https://365datascience.weebly.com/the-best-data-science-blog-2020/computer-vision-projects-with-python

Traveloka: Using Data to Build a Universal Search Engine

Learn how we helped online travel company Traveloka build a universal search engine capable of returning results in multiple product categories.

Traveloka is an online travel company that provides a one-stop platform for a range of ticketing services, including flights, accommodation, and attractions. As one of Southeast Asia’s “unicorn” startups valued at over $1 billion, Traveloka is constantly searching for ways to improve their user experience. As part of this initiative, Traveloka has invested heavily in a number of artificial intelligence and machine learning projects.

With an expanding list of 19 core product offerings, improving search capabilities was key to their continued growth. To do this, Traveloka built a search function to make it easy for users to browse the full range of products from a single search bar.

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We spoke with Deb Goswami, who is directly responsible for Traveloka’s ongoing research, design, and implementation. Deb oversees the machine learning team at Traveloka, whose sole purpose is to implement machine learning solutions. As Deb began to look into data annotation solutions, he found Lionbridge.

“Lionbridge initially stood out because of their capabilities in the regional language space, but we were also impressed by their flexible approach to data annotation. It was clear from early on that they were committed to providing us with a high level of support and eager to align with our project requirements.”

Dr Deb Goswami, Data Science Lead at Traveloka

Getting enough people to collect and annotate data was a large obstacle for the team at Traveloka. Lionbridge developed a comprehensive solution to classify thousands of search queries according to an extensive system of product and sub-product categories.

With Lionbridge’s support, Traveloka’s machine learning team was able to focus on the search engine’s core development work. As a result, Traveloka quickly launched the product with confidence that it was trained using high-quality data and backed by extensive linguistic capabilities.

“From our previous experience, we know how difficult it is to build out effective data annotation teams from scratch. We were extremely pleased with Lionbridge’s ability to scale without compromising on quality or speed, particularly when it came to acting on our feedback. Our partnership has produced some great results and we’re looking forward to more successful releases in the near future.”

Dr. Deb Goswami

Traveloka’s new universal search function allows users to effortlessly search 76 unique product combinations with a single click. With further releases still to come, Traveloka’s algorithm will continue to improve ease-of-use for both their web and app users. You can try out Traveloka’s new search function by downloading the app here.

Want to learn more? Download the full case study.

Don’t forget to give us your ? !

Traveloka: Using Data to Build a Universal Search Engine was originally published in Becoming Human: Artificial Intelligence Magazine on Medium, where people are continuing the conversation by highlighting and responding to this story.

Via https://becominghuman.ai/traveloka-using-data-to-build-a-universal-search-engine-6d968bc8cca0?source=rss—-5e5bef33608a—4

source https://365datascience.weebly.com/the-best-data-science-blog-2020/traveloka-using-data-to-build-a-universal-search-engine

Adversarial Examples in Deep Learning A Primer

Bigger compute has led to increasingly impressive deep learning computer vision model SOTA results. However most of these SOTA deep learning models are brought down to their knees when making predictions on adversarial images. Read on to find out more.

Originally from KDnuggets https://ift.tt/2KvlHZX

source https://365datascience.weebly.com/the-best-data-science-blog-2020/adversarial-examples-in-deep-learning-a-primer

How Data Scientists Can Avoid Lost in Translation Syndrome When Communicating With Management

When it comes to data science projects, the disconnect between business executives and data teams can lead to major tension. Keeping these challenges from arising in the first place through effective communication will help reduce friction with stakeholders.

Originally from KDnuggets https://ift.tt/2UJIp29

source https://365datascience.weebly.com/the-best-data-science-blog-2020/how-data-scientists-can-avoid-lost-in-translation-syndrome-when-communicating-with-management

Cellular Automata in Stream Learning

In this post, we will start presenting CA as pattern recognition methods for stream learning. Finally, we will briefly mention two recent CA-based solutions for stream learning. Both are highly interpretable as their cellular structure represents directly the mapping between the feature space and the labels to be predicted.

Originally from KDnuggets https://ift.tt/3307GJU

source https://365datascience.weebly.com/the-best-data-science-blog-2020/cellular-automata-in-stream-learning

The top courses for aspiring data scientists

Here are four courses that can give you the necessary skills to lead businesses in the 21st century. All of them include Python programming as a course component. Most of them require an undergraduate knowledge of statistics, calculus, linear algebra, and probability, so we recommend checking your course of interest for the specifics.

Originally from KDnuggets https://ift.tt/32VhKUD

source https://365datascience.weebly.com/the-best-data-science-blog-2020/the-top-courses-for-aspiring-data-scientists

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