KDnuggets

SEPTEMBER 9, 2019

This is a collection of 10 interesting resources in the form of articles and tutorials for the aspiring data scientist new to Python, meant to provide both insight and practical instruction when starting on your journey.

Python 122

Python Data Programming Data Science 122

Teradata

SEPTEMBER 11, 2019

AI & Deep Learning allow organizations to maximize player performance while minimizing player risk through better insights from performance and wellness data.

Deep Learning 98

Deep Learning Data 98

Rockset

SEPTEMBER 13, 2019

What Is Grafana? Grafana is an open-source software platform for time series analytics and monitoring. You can connect Grafana to a large number of data sources, from PostgreSQL to Prometheus. Once your data source is connected, you can use a built-in query control or editor to fetch data, and build dashboards from your data source. Grafana is frequently deployed for a wide variety of use cases, including DevOps and AdTech.

PostgreSQL 52

PostgreSQL SQL Building Engineering 52

nodeSWAT

SEPTEMBER 9, 2019

Story about unexpected slowdown during AWS RDS upgrade to AWS Aurora and InnoDB adaptive hash index parameter TL;DR at the end. The parameter. MySQL 5.7 documentation about InnoDB adaptive hash index. Turning this parameter ON enables the database engine to analyze index searches and to automatically adapt to the queries/searches you are running. It does so by making custom indexes for these specific cases, in return making your queries run faster because they can now use the automatically gener

AWS 52

AWS MySQL Database SQL 52

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science

KDnuggets

SEPTEMBER 11, 2019

As compute gets cheaper and time to market for machine learning solutions becomes more critical, we’ve explored options for speeding up model training. One of those solutions is to combine elements from Spark and scikit-learn into our own hybrid solution.

Machine Learning 121

Machine Learning Systems Python 121

Teradata

SEPTEMBER 9, 2019

There are a lot of misperceptions about Teradata. Learn more about what Teradata Vantage really is: a cloud-first integrated data and analytics platform.

Cloud 63

Cloud Data Analytics Data 63

Confluent

SEPTEMBER 13, 2019

Static Membership is an enhancement to the current rebalance protocol that aims to reduce the downtime caused by excessive and unnecessary rebalances for general Apache Kafka ® client implementations. This applies to Kafka consumers, Kafka Connect, and Kafka Streams. To get a better grasp on the rebalance protocol, we’ll examine this concept in depth and explain what it means.

Kafka 21

Kafka Cloud Metadata Process 21

KDnuggets

SEPTEMBER 12, 2019

It is important to distinguish prediction and classification. In many decision-making contexts, classification represents a premature decision, because classification combines prediction and decision making and usurps the decision maker in specifying costs of wrong decisions.

IT 119

IT Machine Learning Data Science Data 119

Netflix Tech

SEPTEMBER 10, 2019

Toby Mao , Sri Sri Perangur , Colin McFarland Another day, another custom script to analyze an A/B test. Maybe you’ve done this before and have an old script lying around. If it’s new, it’s probably going to take some time to set up, right? Not at Netflix. ABlaze: The standard view of analyses in the XP UI Suppose you’re running a new video encoding test and theorize that the two new encodes should reduce play delay, a metric describing how long it takes for a video to play after you press the s

Raw Data 86

Raw Data Python Datasets SQL 86

KDnuggets

SEPTEMBER 13, 2019

While ensembling techniques are notoriously hard to set up, operate, and explain, with the latest modeling, explainability and monitoring tools, they can produce more accurate and stable predictions. And better predictions can be better for business.

Machine Learning 119

Machine Learning 119

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

Engineering

KDnuggets

SEPTEMBER 10, 2019

How does the scikit-learn machine learning library for Python compare to the mlr package for R? Following along with a machine learning workflow through each approach, and see if you can gain a competitive advantage by knowing both frameworks.

Machine Learning 117

Machine Learning Python 117

KDnuggets

SEPTEMBER 12, 2019

There is no such thing as a free lunch in life or data science. Here, we'll explore some science philosophy and discuss the No Free Lunch theorems to find out what they mean for the field of data science.

Data Science 114

Data Science Data Machine Learning 114

KDnuggets

SEPTEMBER 10, 2019

In this post, I am going to be talking about some of the most important graph algorithms you should know and how to implement them using Python.

Algorithm 122

Algorithm Python Data Data Science 122

KDnuggets

SEPTEMBER 9, 2019

In this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.

Machine Learning 111

Machine Learning Data 111

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

Building

KDnuggets

SEPTEMBER 9, 2019

BERT is changing the NLP landscape and making chatbots much smarter by enabling computers to better understand speech and respond intelligently in real-time.

110

110

KDnuggets

SEPTEMBER 13, 2019

This post expands on the NAACL 2019 tutorial on Transfer Learning in NLP organized by Matthew Peters, Swabha Swayamdipta, Thomas Wolf, and Sebastian Ruder. This post highlights key insights and takeaways and provides updates based on recent work.

102

102

KDnuggets

SEPTEMBER 11, 2019

Online hate speech is a complex subject. Follow this demonstration using state-of-the-art graph neural network models to detect hateful users based on their activities on the Twitter social network.

Machine Learning 101

Machine Learning 101

KDnuggets

SEPTEMBER 9, 2019

I am really interested in creating a tight, clean pipeline for disaster relief applications, where we can use something like crowd sourced building polygons from OSM to train a supervised object detector to discover buildings in an unmapped location.

Building 95

Building Data Machine Learning Python 95

Advertisement

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

Project

KDnuggets

SEPTEMBER 9, 2019

In this article, we’ll look at research and model architectures that have been written and developed to do just that using deep learning.

Deep Learning 109

Deep Learning Architecture 109

KDnuggets

SEPTEMBER 12, 2019

It turned out that, if we ask the weak algorithm to create a whole bunch of classifiers (all weak for definition), and then combine them all, what may figure out is a stronger classifier.

Machine Learning 87

Machine Learning Algorithm IT Python 87

KDnuggets

SEPTEMBER 9, 2019

Recently, Alphabet’s subsidiaries Waymo and DeepMind partnered to find a more efficient process to train self-driving vehicles algorithms and their work took them back to one of the cornerstones of our history as species: evolution.

Algorithm 86

Algorithm Process 86

KDnuggets

SEPTEMBER 10, 2019

ODSC has developed a mini-bootcamp, designed to reduce the time and monetary costs of discovering which pathway into data science you should take. In this article, we’ll discuss seven reasons why ODSC’s Mini-Bootcamp might be right for you.

Data Science 82

Data Science Data Designing Education 82

Speaker: Margaret-Ann Seger, Head of Product, Statsig

Experimentation is often seen as an aspirational practice, especially at smaller, fast-moving companies who are strapped for time and resources. So, how can you get your team making decisions in a more data-driven way while continuing to remain lean and maintaining ship velocity? In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating

Building

KDnuggets

SEPTEMBER 11, 2019

Data Driven Government is coming to Washington, DC, Sep 26, and includes a stellar lineup of experts who will share the emerging trends and best practices of government agencies in the current use of data analytics to enhance mission outcomes. Use code KDNUGGETS to get 15% off.

Government 79

Government Data Analytics Data Coding 79

KDnuggets

SEPTEMBER 13, 2019

I am a Git god, why do I need another version control system for Machine Learning Projects?

Machine Learning 104

Machine Learning Datasets Data Science Project 104

KDnuggets

SEPTEMBER 12, 2019

This article explains the Support Vector Machines (SVM) algorithm in an easy way.

Algorithm 105

Algorithm Machine Learning 105

KDnuggets

SEPTEMBER 12, 2019

Io-Tahoe, a pioneer in Smart Data Discovery and AI-Driven Data Catalog products, has announced that Clearsense, a scalable data platform as a service built for healthcare, has chosen the smart data discovery platform to automatically discover and catalog relationships across immense amounts of medical and clinical data.

Healthcare 68

Healthcare Medical Data 68

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

Certification

KDnuggets

SEPTEMBER 10, 2019

Also: Top Handy SQL Features for Data Scientists; 12 NLP Researchers, Practitioners & Innovators You Should Be Following; Knowing Your Neighbours: Machine Learning on Graphs.

Machine Learning 63

Machine Learning SQL Data 63

KDnuggets

SEPTEMBER 9, 2019

Also: Python Libraries for Interpretable Machine Learning; TensorFlow vs PyTorch vs Keras for NLP; Advice on building a machine learning career and reading research papers by Prof. Andrew Ng; Object-oriented programming for data scientists: Build your ML estimator.

Machine Learning 51

Machine Learning Python Programming Data 51

KDnuggets

SEPTEMBER 11, 2019

How one person overcame rejections applying to Data Scientist positions by getting actual data on who is getting hired; Advice from Andrew Ng on building ML career and reading research papers; 10 Great Python resources for Data Scientists; Python Libraries for Interpretable ML,

Python 51

Python Data Building 51

KDnuggets

SEPTEMBER 11, 2019

Python Libraries for Interpretable Machine Learning; How #AI will transform #healthcare (and can it fix US healthcare system?); Building Recommendation System - an overview ; I wasn't getting hired as a Data Scientist. So I sought data on who is.

Healthcare 49

Healthcare Python Machine Learning Systems 49

Advertisement

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.

Building