Remove Machine Learning Remove Product Management Remove Software Engineering Remove Weak Development Team
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All about Machine Learning

Hacker Earth Developers Blog

In our third episode of Breaking 404 , we caught up with Srivatsan Ramanujam, Director of Software Engineering: Machine Learning, Salesforce to discuss everything about Machine Learning and the best practices for ML engineers to excel in their careers. At the time I was a software engineer.

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What you need to know about product management for AI

O'Reilly Media - Ideas

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). You already know the game and how it is played: you’re the coordinator who ties everything together, from the developers and designers to the executives.

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Why I Became a Software Engineer at Modus Create

Modus Create

Now imagine running an omnichannel retail company overhauling its bottom line by providing machine learning recommendations based on time series data. The kid running the lemonade stand is expected to have some working knowledge of lemonade, otherwise, how would they sell their product and run a lemonade business. Conclusion.

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Bringing an AI Product to Market

O'Reilly Media - Ideas

The Core Responsibilities of the AI Product Manager. Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Identifying the problem. Agreeing on metrics.

Marketing 145
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What is digital transformation? A necessary disruption

CIO

Digital transformation defined Digital transformation has become a catchall term for describing the implementation of digital technologies to re-engineer existing processes or develop new services that better engage customers, support employees, improve business operations, and drive business value to the organization’s bottom line.

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Check out these startups from Pear’s Demo Day (there’s usually a breakout or two in the bunch)

TechCrunch

As notably, despite introducing a far smaller number of teams to investors than Y Combinator and more renowned accelerator programs, there always seem to be at least one or two projects in Pear’s Demo Day mix that turn into actual, sustainable and, sometimes, sizable companies. It has some others it can, and does, boast about, too.

CTO Coach 186
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Data Architect: Role Description, Skills, Certifications and When to Hire

Altexsoft

What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority. machine learning and deep learning models; and business intelligence tools. Let’s discuss and compare them to avoid misconceptions.

Data 87