KDnuggets

JANUARY 2, 2020

Time series forecasting is a technique for the prediction of events through a sequence of time. In this post, we will be taking a small forecasting problem and try to solve it till the end learning time series forecasting alongside.

IT 151

IT Python 151

Data Engineering Podcast

DECEMBER 30, 2019

Summary DataDog is one of the most successful companies in the space of metrics and monitoring for servers and cloud infrastructure. In order to support their customers, they need to capture, process, and analyze massive amounts of timeseries data with a high degree of uptime and reliability. Vadim Semenov works on their data engineering team and joins the podcast in this episode to discuss the challenges that he works through, the systems that DataDog has built to power their business, and how

Process 100

Process Building Hadoop Java 100

Teradata

DECEMBER 29, 2019

How do you organize your business for analytics? Here are six steps your enterprise should take when creating an analytics team. Read more!

59

59

Confluent

DECEMBER 30, 2019

During the holiday season, it’s a particularly relevant time to pause, reflect, and celebrate, both the days past and those ahead. Here at Confluent, it’s a noticeably nostalgic moment, given […].

19

19

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

DECEMBER 31, 2019

With so many buzzwords surrounding AI and machine learning, understanding which can bring business value and which are best left in the lab to mature is difficult. While machine learning offers significant power in driving digital transformations, a business must start with the right questions and leave the math to the development teams.

Data Science 145

Data Science Machine Learning Data 145

KDnuggets

JANUARY 3, 2020

Why do most data scientists love Python? Learn more about how so many well-developed Python packages can help you accomplish your crucial data science tasks.

Data Science 151

Data Science Python Data Programming Language 151

KDnuggets

DECEMBER 30, 2019

For those of you in a hurry and interested in ultralearning (which should be all of you), this recap reviews the approach and summarizes its key elements -- focus, optimization, and deep understanding with experimentation -- geared toward learning Data Science.

Data Science 103

Data Science Data IT 103

KDnuggets

JANUARY 3, 2020

This post presents a pipeline of building a KNN model in R with various measurement metrics.

Building 136

Building 136

KDnuggets

JANUARY 2, 2020

Delivering accurate insights is the core function of any data scientist. Navigating the development road toward this goal can sometimes be tricky, especially when cross-collaboration is required, and these lessons learned from building a search application will help you negotiate the demands between accuracy and speed.

Data 90

Data Building Engineering 90

KDnuggets

DECEMBER 31, 2019

A Gentle Introduction to #Math Behind #NeuralNetworks; Learn How to Quickly Create UIs in Python; I wanna be a data scientist, but. how!?; I created my own deepfake in two weeks.

Python 70

Python Data 70

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

DECEMBER 31, 2019

AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.

Systems 87

Systems 87

KDnuggets

DECEMBER 30, 2019

AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.

Systems 78

Systems 78

KDnuggets

JANUARY 3, 2020

The gender gap can extend to the lack of equal representation in certain industries or career paths, and there's an extraordinarily long way to go before people will be on equal footing in the labor market. Human resources professionals can rely on data analytics to make progress.

Data Science 53

Data Science Data Analytics Data 53

KDnuggets

DECEMBER 30, 2019

Also: Let’s Build an Intelligent Chatbot; 10 Best and Free Machine Learning Courses, Online; Build Pipelines with Pandas Using pdpipe; Alternative Cloud Hosted Data Science Environments.

Machine Learning 52

Machine Learning Data Science Cloud Data 52

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

Teradata

DECEMBER 29, 2019

How do you organize your business for analytics? Here are six steps your enterprise should take when creating an analytics team. Read more!

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58

Teradata

DECEMBER 29, 2019

Are you a budding data scientist? Learn why Kaggle only offers a limited view of data science and is not the optimal place to learn data science skills.

Data Science 8

Data Science Data 8