Machine learning edge devices: benchmark report

Why edge computing? Humans are generating and collecting more data than ever. We have devices in our pockets that facilitate the creation of huge amounts of data, such as photos, gps coordinates, audio, and all kinds of personal information we consciously and unconsciously reveal. Moreover, not only are we individuals generating data for personal reasons, but we’re also collecting data unbeknownst to us from traffic and mobility control systems, video surveillance units, satellites, smart cars, and an infinite array of smart devices.

Deep in the dark: enhancing malware traffic detection with deep learning

The IEEE Symposium on Security and Privacy (IEEE S&P) is one of the top-tier conferences in computer security and electronic privacy. This year, the IEEE S&P was held in May, in San Francisco. It was not a regular edition, as this flagship conference marked its 40th anniversary. This year’s symposium was a special celebration that included a plenary session with some exceptional panelists from the S&P community, Test of Time awards for papers that have made a lasting impact on the field, and even an amazing birthday cake!

Recap: our first machine learning meetup in San Francisco

Lately, our team has been invited to give several talks at conferences, workshops and company events all around the world. As we got great feedback from the audience of these events, we felt like organizing our very own machine learning event for our partners and friends in San Francisco. We could have an open space to share experiences and directly talk about the opportunities behind machine learning. Event flyer of our first machine learning meetup in SF.

Embedded Vision Summit 2019: My talk and takeaways

As a machine learning engineer, building solutions in the vision and deep learning fields, I’d always had my eye on the Embedded Vision Summit, a leading computer vision conference taking place yearly in Silicon Valley. When I found out I had been invited to speak at the 2019 edition of the conference taking place May 18-21, I was obviously very excited. This was going to be an amazing opportunity for me to share my experiences in the field, and of course I was all in.

Transform 2019 Conference — Accelerate your business with AI

Our effort spent curating the list of machine learning conferences over the last two years has proven that there are an evermore increasing number of interesting machine learning conferences taking place around the world. While they all deserve mention and are worth attending, there are some conferences that we think are especially noteworthy given their great lineup of speakers and programs and that we’ve tagged Tryolabs’ Picks. One of our favorite conferences is Transform 2019, which takes place July 10-11 at the Union Square Hilton, in Downtown San Francisco.

Can you beat this pricing algorithm?

This post was written in collaboration with Facundo Parodi, Research & Machine Learning Engineer at Tryolabs. Deciding on the best price for a product or service you’re providing, in order to maximize business profit, is not a trivial problem, not at all. Actually, it’s always ongoing, since you can never tell if the price you chose is better than others you didn’t. Even if you try other prices, market conditions may change, as they frequently do.

My talk at the Tom Tom Festival 2019

In January, I got the great news that I had been invited to give a talk at the sold out Applied Machine Learning Conference (AMLC), which would take place at the Tom Tom Summit & Festival in Charlottesville (Virginia) in April. I had heard great things about the 2018 edition and was eager to know Charlottesville, so I immediately accepted the invitation. 🤗 That's me, talking about ConvNets at the Tom Tom Festival 2019 About Tom Tom Summit & Festival The Tom Tom Summit & Festival is an annual event with the following mission:

5 actionable steps to get your data ready for price optimization with ML

There’s some great theory around about pricing with machine learning (ML) and, in particular, the importance of the “right” data to build a successful ML model. In practice, though, we’ve seen that there’s a lot of confusion around the data types and formats that retailers can use to automate pricing or to implement price optimization systems using ML. That’s why we came up with 5 steps every company can take to prepare its data for price optimization.

11 questions to ask before starting a successful Machine Learning project

Machine Learning (ML) algorithms are changing nearly every industry. They’re increasing productivity, boosting sales and helping us make more informed decisions. Many organizations are either already leveraging the power of ML, or have it laid out in their roadmap as an opportunity worth pursuing. Trouble is, ML is complex and you might ask yourself what you need to consider when starting a ML project. Asking that question is absolutely right!

The major advancements in Deep Learning in 2018

Deep learning has changed the entire landscape over the past few years. Every day, there are more applications that rely on deep learning techniques in fields as diverse as healthcare, finance, human resources, retail, earthquake detection, and self-driving cars. As for existing applications, the results have been steadily improving. At the academic level, the field of machine learning has become so important that a new scientific article is born every 20 minutes.

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