Best Practices for Building Computer Vision Models
You can't build self-driving cars or computer generated films without computer vision. And for that you need copious amounts of image data. Luis Bermudez is a Research Scientist at Intel's Applied Machine Learning team, where he solves customer problems with ML solutions to significantly accelerate existing workflows.
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Data Science Webinars

Effective Data Science in the Enterprise

December 4, 2020 at 1:00pm Eastern Time

From navigating organizational structures to leveraging data lifecycles and workflows, Lisa will provide advice on how to grow a career in enterprise data and analytics based on her 16 year career in the industry.

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Decision Science: Translating Data Insights to Corporate Decision Making

November 24, 2020 at 1:00pm Eastern Time

What are the common pitfalls data scientists face when trying to influence decisions, both operational and strategic? 'Decision science' guides corporate decision making, and can be used to make smarter decisions such as which sales lead to follow or which marketing tactic to deploy.

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Navigating a Data Career: Academia, Data Science, Product Management

November 17, 2020 at 12:00pm Eastern Time

Join Jesse Day as he discusses his evolution from academic research, to data science, to product management. This talk covers transitioning from a PhD to data science, working at a startup, and much more.

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Moving from Software Engineering to Machine Learning

November 11, 2020 at 12:00pm Eastern Time

Matthew Beleck discusses the differences between software engineering and ML projects. Data projects often present unique challenges to engineers, as data quality and availability can impact your ability to complete a product build.

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Best Practices for NLP Data Collection and Design

November 10, 2020 at 6:00pm Eastern Time

You can't build NLP-powered products and services without robust, detailed data sets. Unfortunately, building such data sets can be time consuming and expensive; a poorly designed data set will also prevent your models from actually helping users. Ivan Lee discusses best practices for data set design and labelling.

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Tips and Perspective on Starting Your Data Science Career

November 5, 2020 at 12:00pm Eastern Time

Data Science is a broad field with numerous core competencies and specializations. In this talk, Justin explores some of necessary skills for transitioning from learning data science to doing data science in an R&D setting, in both government and private industry.

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Building Products Powered by Data and ML

October 28, 2020 at 6:00pm Eastern Time

Launching data products using a traditional product approach is challenging. Amber Foucault will share the importance of creating "data networks" that can power multiple applications and features, and discuss how you must think differently about validation when building data products.

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Help Your Manager Help You Build the Career You Want

October 26, 2020 at 1:00pm Eastern Time

Jessica Hastings, VP of Analytics at Betterment, will talk about how you can maximize this relationship and empower your manager to be your best advocate. She’ll share insight into the manager mindset, strategies for tailoring formal and informal communication with your manager, and suggestions for how to refine your own vision for what you want to achieve.

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Starting and Managing a Career in Natural Language Processing

October 22, 2020 at 6:00pm Eastern Time

Natural Language Processing (NLP) helps companies understand documents, emails, and other unstructured text data. It's a fast-growing field with companies hiring analysts, product managers, and researchers to help launch NLP-driven products. This webinar will discuss trends in NLP and ways you can start a career focusing on this popular area of machine learning.

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Building and Leveraging Your Online Profile

October 21, 2020 at 6:00pm Eastern Time

Join Andrew Savage, Data Recruiter at Faire, in this talk about how to stand out in the online crowd of data professionals. This session is for job seekers who are ready to apply for jobs but are looking for ways to better stand out in the crowd on LinkedIn and other online tools.

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Marketing Analytics in the CPG Industry

October 14, 2020 at 1:00pm Eastern Time

Justin Mathew is a marketing data scientist in the oral care business at Proctor & Gamble. He will join us for a conversation about how he started his career and how he brings data science to the forefront of marketing and media within the CPG industry.

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From Physics PhD to Applied ML

October 13, 2020 at 2:00pm Eastern Time

Jorge Escobedo completed a PhD in String Theory, and then cofounded a YC-backed AI-focused customer data company. After a successful exit, Jorge Escobedo joined Drop as the Head of Data and Machine Learning. He now leads their technology function as VP of Engineering.

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Hybrid Data Scientists

October 9, 2020 at 2:00pm Eastern Time

"Hybrid data scientists" are people who have a strong set of experiences in non-analytics and combine this experience with data/analytics to build unique career paths. Andrea Yip will discuss her interviews with logistics experts turned data scientists, biotech researchers who have moved into marketing analytics, and more.

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Career Advice

Data Portfolios from the Phase AI Community

January 20, 2021

Data portfolios showcase the unique talents of a data professional. Portfolios come in many different shapes and forms. This post shows examples of data portfolios from the Phase AI community.

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Book Review: Machine Learning Design Patterns

January 6, 2021

An oft-overlooked area of data science is the actual architecture of machine learning systems. This book provides an overview of common design patterns for planning, building, and scaling ML systems.

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Skills and Qualities of Top Tier ML Researchers

December 8, 2020

ML Researchers don't just need to build models, they need to understand how to define problems, build data sets, and implement research papers. Learn what defines top tier researchers.

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Six tips for applying for jobs on our data science jobs board

December 1, 2020

The Phase AI data science jobs board has dozens of new jobs posted daily. Learn how you can stand out in the crowd of applicants with these six tips.

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The Best Data Portfolios on the Web

November 23, 2020

Many of you asked for examples of stellar portfolios, so we searched the web and found diverse portfolios that demonstrate how folks have taken different approaches to showcasing their work.

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A data recruiter's guide to standing out of the online crowd

November 10, 2020

Data science is a crowded industry. Standing out and getting noticed by potential employers and collaborators can be challenging. Here are 7 tips on how to get your accomplishments as a data professional noticed online.

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Preparing for your first screening call for a data role

November 4, 2020

A first step in any hiring process is the initial screening call. Here are our top recommendations for preparing for your next screening call...

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The Power of Hybrid Data Scientists

October 29, 2020

“Hybrid” data scientists are individuals who have made a pivot into data science (as scientists, analysts, engineers, etc.) from a non-data profession. It’s a powerful way to distinguish yourself from other applicants.

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Put together a data science portfolio and get noticed

October 20, 2020

An important part of seeking a data-oriented job is putting together a data science portfolio. Portfolios help candidates stand out to hiring managers and potential companies they could work at.

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