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Videos by: newcircle

The Basics of ROS Applied to Self-Driving Cars

5 days ago
Anthony Navarro covers a brief overview of the ROS (Robot Operating System) architecture and how we would begin using it on our self-driving car project. ROS is a framework used for robotics around the world. With the emergence of self-driving cars, many companies have helped moved ROS from an academic tool to a core component […]

pDB: Abstraction for Modeling Predictive Machine Learning Problems

1 week ago
Balaji Rengarajan does a brief overview of modeling machine learning problems using Celect’s pDB framework. He demonstrates how disparate predictive problems can be expressed using a common pDB language. Balaji Rengarajan is responsible for architecting and engineering key aspects of the cloud- agnostic data science platform based on Celect’s pDB framework for non-parametric machine learning. […]

Building (Better) Data Pipelines with Apache Airflow

2 weeks ago
In this session, Sid Anand talks about Apache Airflow, an up-and-coming platform to programmatically author, schedule, manage, and monitor workflows. Airflow’s design requires users to define DAGs (directed acyclic graphs) a.k.a. workflows in Python code, so that DAGs can be managed via the same software engineering principles and practices used to manage any other code. […]

Transmogrification: The Magic of Feature Engineering

2 weeks ago
Machine learning algorithms often take center stage in machine learning and AI. However, in the real world, 90% of the time spent building models goes into creating the mythical perfect numeric matrix of features, to feed into the chosen algorithm. Every machine learning team repeats the same effort, reinventing the wheel once again. In this […]

Continuous Delivery for AI Applications

3 weeks ago
Asif Khan talks about how to connect the workflow between the data scientists and DevOps. He explores basic continuous integration and delivery concepts and how they can be applied to deep learning models. Using a number of AWS services, he showcases how we can take the output of a deep learning model and deploy it […]

Serverless for Data Science

3 weeks ago
Mike Lee Williams talks about the basic idea behind serverless cloud architecture, and how to deploy a very simple web application to AWS Lambda using Zappa. He then looks in detail at PyWren, an ultra-lightweight alternative to heavy big data distributed systems such as Spark. Mike Lee Williams is a Research Engineer at Cloudera Fast […]

TensorBoard: Visualizing Learning

4 weeks ago
Machine learning models, especially deep learning ones, can be complex. Chi Zeng walks us through how to debug, monitor, and examine the decisions of a TensorFlow-based model using the TensorBoard suite of visualizations. Chi Zeng works on the TensorBoard suite of visualizations within Google Brain. This video was recorded at 2018: The next […]

A/B Testing for Logistics: It All Depends

1 month ago
In this talk, Jingjie Xiao explains how Instacart A/B tests changes in the logistics system where neither customers nor shoppers are independent. She also discusses how multivariate regression is used to expedite their pace of innovation. Jingjie Xiao is a data scientist on the delivery logistics team at Instacart. This video was recorded at […]

Tooling & Setup for My Neural Network

1 month ago
In this talk, Martin Gorner talks about the toolset that he uses, both to run multiple training experiments in parallel and visualize their outcomes: Tensorflow, Google Cloud ML Engine, Tensorboard. This video was recorded at 2018: The next QCon is in New York, June 25-29, 2018. Check out the tracks and speakers: […]

PyTorch by Example

1 month ago
In this talk, Jendrik Joerdening talks about PyTorch, what it is, how to build neural networks with it, and compares it to other frameworks. Jendrik Joerdening is a Data Scientist at Aurubis. This video was recorded at 2018: The next QCon is in New York, June 25-29, 2018. Check out the tracks and […]

The Paved PaaS to Microservices at Netflix

1 month ago
Download the slides & audio at InfoQ: Yunong Xiao discusses how Netflix standardizes common functionality like service discovery, configuration, metrics, logging, and RPC, across services. These patterns, while described in a Netflix context, can be broadly applicable to increase both reliability and velocity of your microservices architecture. This presentation was recorded at QCon New […]

When Do You Use Machine Learning vs. a Rules Based System?

1 month ago
Soups Ranjan provides examples of applications where machine learning makes sense and when it doesn’t, and gives examples from real-world applications in the risk domain (anti-fraud, cyber security, account takeover detection). Soups Ranjan is the Director of Data Science at Coinbase, one the largest bitcoin exchanges in the world, where he manages the Risk & […]