AI News, BOOK REVIEW: Working at BigML
- On Thursday, June 7, 2018
- By Read More
Working at BigML
We embrace distributed teams and like to work remotely so location is irrelevant for any position at BigML, but we'll do our best to motivate you to temporarily, or permanently, move to Corvallis (Oregon, US) or Valencia (Spain) to work closer to other team members.
Apart from major new algorithms and data manipulation capabilities, we make countless enhancements to existing features to improve on our category leading ease of use, programmability and scalability.
All of this creates the challenge of being able to educate our users quickly to maximize the adoption and ongoing engagement with BigML by clearly communicating complex and technical information with your initiative.
Sending off the BigML #Summer2017Interns
I learned new technologies and had opportunities to practice my communication skills by giving presentations and having discussions with my supervisors, experts in the field, and the other staff within and outside BigML.
I had little knowledge about Machine Learning going in my internship, but I have learned a lot about it throughout my time at in BigML, and it was eye-opening to see its power to revolutionize the marketing world and many other industries.
I do everything related to design and I usually spend my time in web design and graphic design, so thanks to BigML I have improved my skills in HTML and CSS.
Therefore, working at BigML is the perfect experience to be part of the change and start your career in an amazing way.My name is Mohan Kumar Janapareddi, and I graduated from Ferris State University in the Information Security and Intelligence program.
We worked on building a dynamic website where users can easily make predictions for selected features by simply uploading their data to this website.
Overall, working at BigML has been a great opportunity to strengthen my technical knowledge of Machine Learning and programming.My name is Ryan Alder, and I worked at BigML as an intern for just over a month this summer.
I did not know much about Machine Learning when I first joined, and this internship has taught me a great deal regarding what actually happens behind the scenes, and how companies such as BigML are able to take a dataset and convert it accurately into predictions.
Making Machine Learning Work for B2C RevenueOptimization
Today’s post about how BigML helps B2C companies optimize revenue-building initiatives is written by Seamus Abshere, Chief Technology Officer at Faraday.io, as the fourth of our blog post series authored by the speakers at the upcoming 2ML event.
At Faraday, we’re now seeing a wealth of companies fundamentally altering their industry dynamics with innovative, data-driven actions handled by advanced Machine Learning algorithms rather than stale, hard-coded business rules.
Although there are success stories to celebrate and Machine Learning tools are becoming more accessible than ever before, many companies still struggle to successfully operationalize the technology for a number of reasons: We understand that acquiring, managing, and implementing the resources and processes needed to operationalize Machine Learning can be daunting, so we bundled it all up into a simple, user-friendly platform designed for non-data scientists.
- On Monday, July 15, 2019
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