Remove Book Remove Deep Learning Remove Statistics Remove Testing
article thumbnail

Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model.

article thumbnail

Bringing an AI Product to Market

O'Reilly on Data

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. Ethics and Data Science is a short book that helps developers think through data problems, and includes a checklist that team members should revisit throughout the process.

Marketing 363
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Use of Machine Learning to Make Money on Android Monetization

Smart Data Collective

Machine Learning Technology Can Be Ideal for Better Monetizing Your Android Apps. The statistic shows that users routinely open 4-6 applications every day. Different apps allow us to chat with friends, order food delivery, book a taxi, and find the best way to the office. Think about your audience.

article thumbnail

Where Programming, Ops, AI, and the Cloud are Headed in 2021

O'Reilly on Data

This study is based on title usage on O’Reilly online learning. The data includes all usage of our platform, not just content that O’Reilly has published, and certainly not just books. More traditional modes also saw increases: usage of books increased by 11%, while videos were up 24%. AI, Machine Learning, and Data.

article thumbnail

Themes and Conferences per Pacoid, Episode 9

Domino Data Lab

For example, in the case of more recent deep learning work, a complete explanation might be possible: it might also entail an incomprehensible number of parameters. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have.

article thumbnail

Themes and Conferences per Pacoid, Episode 7

Domino Data Lab

O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). I’m here mostly to provide McLuhan quotes and test the patience of our copy editors with hella Californian colloquialisms. The data types used in deep learning are interesting.

article thumbnail

Data Science at The New York Times

Domino Data Lab

A “data scientist” might build a multistage processing pipeline in Python, design a hypothesis test, perform a regression analysis over data samples with R, design and implement an algorithm in Hadoop, or communicate the results of our analyses to other members of the organization in a clear and concise fashion.