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34:52
Culture & Methods Follow 846 Followers

Creating High-Performance Teams Using the Human Full Stack

Posted by Marina Chiovetti  on  Oct 21, 2018 Posted by Marina Chiovetti Follow 1 Followers , James Brett Follow 2 Followers  on  Oct 21, 2018

James Brett and Marina Chiovetti discuss the human elements that impact a team’s ability to create and respond to disruption using the Human Full Stack model.

41:12
AI, ML & Data Engineering Follow 1068 Followers

Deep Learning for Application Performance Optimization

Posted by Zoran Sevarac  on  Aug 22, 2018 Posted by Zoran Sevarac Follow 0 Followers  on  Aug 22, 2018

Zoran Sevarac presents his experience and best practice for autonomous, continuous application performance tuning using deep learning.

33:49
AI, ML & Data Engineering Follow 1068 Followers

Counterfactual Evaluation of Machine Learning Models

Posted by Michael Manapat  on  May 10, 2018 Posted by Michael Manapat Follow 2 Followers  on  May 10, 2018

Michael Manapat discusses how Stripe evaluates and trains their machine learning models to fight fraud.

49:13
AI, ML & Data Engineering Follow 1068 Followers

TensorFlow: Pushing the ML Boundaries

Posted by Magnus Hyttsten  on  Apr 25, 2018 Posted by Magnus Hyttsten Follow 0 Followers  on  Apr 25, 2018

Magnus Hyttsten talks about how Google uses Machine Learning to address problems that were not solvable a year ago, looking at models and how they can be built.

39:06
AI, ML & Data Engineering Follow 1068 Followers

Deep Learning Applications in Business

Posted by Diego Klabjan  on  May 07, 2017 Posted by Diego Klabjan Follow  Followers  on  May 07, 2017

Diego Klabjan discusses models, implementations, and challenges developing applications for trading, forecasting, and healthcare, detailing relevant models and issues adopting and deploying them.

46:36
AI, ML & Data Engineering Follow 1068 Followers

Products and Prototypes with Keras

Posted by Micha Gorelick  on  Apr 08, 2017 Posted by Micha Gorelick Follow 0 Followers  on  Apr 08, 2017

Micha Gorelick shows how to build a working product with Keras, a high-level deep learning framework, discussing design decisions, and demonstrating how to train and deploy a model.

38:49
AI, ML & Data Engineering Follow 1068 Followers

Using Bayesian Optimization to Tune Machine Learning Models

Posted by Scott Clark  on  Feb 07, 2017 Posted by Scott Clark Follow 0 Followers  on  Feb 07, 2017

Scott Clark introduces Bayesian Global Optimization as an efficient way to optimize ML model parameters, explaining the underlying techniques and comparing it to other standard methods.

44:51
Culture & Methods Follow 846 Followers

There is No Spotify Model

Posted by Marcin Floryan  on  Oct 23, 2016 Posted by Marcin Floryan Follow 0 Followers  on  Oct 23, 2016

Marcin Floryan discusses the Spotify engineering culture.

44:42
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Beyond Projects - Why Projects Are Wrong and What to Do Instead

Posted by Allan Kelly  on  Feb 07, 2015 1 Posted by Allan Kelly Follow 2 Followers  on  Feb 07, 2015 1

Allan Kelly examines the project model and shows why it does not match software development, outlining an alternative to the project model and what companies need to do to achieve it.

33:59
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Data-Driven Software Engineering

Posted by Jevgeni Kabanov  on  Sep 27, 2014 1 Posted by Jevgeni Kabanov Follow 0 Followers  on  Sep 27, 2014 1

Jevgeni Kabanov discusses the results of a research on a delivering software model, the tools involved and the model itself, concluding on what one can expect from using certain tools.

38:46
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Machine Learning for Relevance and Serendipity

Posted by Jenny Finkel  on  Oct 30, 2013 Posted by Jenny Finkel Follow 1 Followers  on  Oct 30, 2013

Jenny Finkel showcases Prismatic's use of machine learning and language processing to provide targeted content to their users based on a model built on users' way of interacting with their website.

49:55
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The Functional Database

Posted by Rich Hickey  on  Oct 11, 2013 6 Posted by Rich Hickey Follow 56 Followers  on  Oct 11, 2013 6

Rich Hickey discusses how a functional database can impact the programming model, using Datomic as an example, but the principles apply to other systems using an immutable database.

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