Data science for lazy people, Automated Machine Learning by Diego Hueltes at Big Data Spain 2017

Dec 4, 20170 likes1,255 views

The power of this new set of tools for Data Science. Is really easy to start applying these technics in your current workflow. https://www.bigdataspain.org/2017/talk/data-science-for-lazy-people-automated-machine-learning Big Data Spain 2017 November 16th - 17th Kinépolis Madrid

Data science for lazy people, Automated Machine Learning by Diego Hueltes at Big Data Spain 2017

Irene Gonzálvez is a product manager at Spotify who discusses data quality. Spotify has over 140 million monthly active users and more than 30 million songs. Data enables recommendations, advertising, and payments but data quality problems cost businesses $600 billion per year. Irene discusses Spotify's focus on data quality through tools like DataMon, Data Counters, and MetriLab. She advocates building an algorithm library for anomaly detection and a Spotify-wide strategy to identify critical datasets and ensure they are high quality.

Scaling a backend for a big data and blockchain environment by Rafael Ríos at...Big Data Spain

This document discusses scaling the backend of a financial platform for big data and blockchain. It describes challenges integrating big data using Apache Spark and Cassandra for tasks like predictive modeling, recommendations, and credit scoring. It also covers using a microservices architecture with Spring Cloud, Docker, and Kubernetes for deployment. Blockchain integration involves a private Ethereum network on Kubernetes for tokenization and a connection to the public Ethereum mainnet using Infura for payments and transfers.

AI: The next frontier by Amparo Alonso at Big Data Spain 2017Big Data Spain

Disaster Recovery for Big Data by Carlos Izquierdo at Big Data Spain 2017Big Data Spain

Presentation: Boost Hadoop and Spark with in-memory technologies by Akmal Cha...Big Data Spain

Apache Ignite is an in-memory platform that can accelerate Hadoop and Spark workloads by storing data in memory. It provides a distributed in-memory file system (IGNITE) that can be used as a secondary storage layer for Hadoop. For Spark, Ignite allows sharing RDDs across jobs by storing them in an Ignite cache, avoiding the need to write to disk between jobs. The IgniteContext class provides the main entry point for integrating Spark and Ignite, allowing Spark jobs to read from and write RDD data directly to Ignite caches.

Training Deep Learning Models on Multiple GPUs in the Cloud by Enrique Otero ...Big Data Spain

This document discusses training deep learning models using multiple GPUs in the cloud. It covers the challenges of distributed training including data bottlenecks, communication bottlenecks, and scaling batch sizes and learning rates. It provides benchmarks for frameworks like MXNet and TensorFlow on AWS and discusses the impact of infrastructure like GPU type and interconnect bandwidth on training performance and efficiency. It also analyzes the costs of using different cloud platforms for deep learning training.

Unbalanced data: Same algorithms different techniques by Eric Martín at Big D...Big Data Spain

State of the art time-series analysis with deep learning by Javier Ordóñez at...Big Data Spain

Trading at market speed with the latest Kafka features by Iñigo González at B...Big Data Spain

Unified Stream Processing at Scale with Apache Samza by Jake Maes at Big Data...Big Data Spain

The Analytic Platform behind IBM’s Watson Data Platform by Luciano Resende a...Big Data Spain

Artificial Intelligence and Data-centric businesses by Óscar Méndez at Big Da...Big Data Spain

Why big data didn’t end causal inference by Totte Harinen at Big Data Spain 2017Big Data Spain

Meme Index. Analyzing fads and sensations on the Internet by Miguel Romero at...Big Data Spain

Vehicle Big Data that Drives Smart City Advancement by Mike Branch at Big Dat...Big Data Spain

End of the Myth: Ultra-Scalable Transactional Management by Ricardo Jiménez-P...Big Data Spain

Attacking Machine Learning used in AntiVirus with Reinforcement by Rubén Mart...Big Data Spain

More people, less banking: Blockchain by Salvador Casquero at Big Data Spain ...Big Data Spain

Make the elephant fly, once again by Sourygna Luangsay at Big Data Spain 2017Big Data Spain

Feature selection for Big Data: advances and challenges by Verónica Bolón-Can...Big Data Spain

Deep reinforcement learning : Starcraft learning environment by Gema Parreño ...Big Data Spain

End-to-End “Exactly Once” with Heron & Pulsar by Ivan Kelly at Big Data Spain...Big Data Spain

A Deep Learning use case for water end use detection by Roberto Díaz and José...Big Data Spain

Tuning Java Driver for Apache Cassandra by Nenad Bozic at Big Data Spain 2017Big Data Spain

Spark Streaming + Kafka 0.10: an integration story by Joan Viladrosa Riera at...Big Data Spain

This document provides an overview of Apache Kafka and Spark Streaming and their integration. It discusses: - What Apache Kafka is and how it works as a publish-subscribe messaging system with topics, partitions, producers, and consumers. - What Apache Spark Streaming is and how it provides streaming data processing using micro-batching and leveraging Spark's APIs and engine. - The evolution of the integration between Kafka and Spark Streaming, from using receivers to the direct approach without receivers in Spark 1.3+. - Details on how to use the new direct Kafka integration in Spark 2.0+ including location strategies, consumer strategies, and committing offsets directly to Kafka. - Considerations around at-least

Keeping your Enterprise’s Big Data Secure by Owen O’Malley at Big Data Spain ...Big Data Spain

Bayesian inference and big data: are we there yet? by Jose Luis Hidalgo at Bi...Big Data Spain

Bayesian inference has a reputation of being complex and only applicable to fairly small datasets. Very recent developments may be chaining that, and we are starting to see some successful real world application of Bayesian inference to very large datasets, and some tools to make it accessible to many more data science practitioners. https://www.bigdataspain.org/2017/talk/bayesian-inference-and-big-data-are-we-there-yet Big Data Spain 2017

Apache MXNet Distributed Training Explained In Depth by Viacheslav Kovalevsky...Big Data Spain

Complete Guide to Advanced Logistics Management Software in Riyadh.pdfSoftware Company

Explore the benefits and features of advanced logistics management software for businesses in Riyadh. This guide delves into the latest technologies, from real-time tracking and route optimization to warehouse management and inventory control, helping businesses streamline their logistics operations and reduce costs. Learn how implementing the right software solution can enhance efficiency, improve customer satisfaction, and provide a competitive edge in the growing logistics sector of Riyadh.

Big Data Analytics Quick Research Guide by Arthur MorganArthur Morgan

This is a Quick Research Guide (QRG). QRGs include the following: - A brief, high-level overview of the QRG topic. - A milestone timeline for the QRG topic. - Links to various free online resource materials to provide a deeper dive into the QRG topic. - Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic. QRGs planned for the series: - Artificial Intelligence QRG - Quantum Computing QRG - Big Data Analytics QRG - Spacecraft Guidance, Navigation & Control QRG (coming 2026) - UK Home Computing & The Birth of ARM QRG (coming 2027) Any questions or comments? - Please contact Arthur Morgan at [email protected]. 100% human made.

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