KDnuggets

JANUARY 8, 2020

The standard job description for a Data Scientist has long highlighted skills in R, Python, SQL, and Machine Learning. With the field evolving, these core competencies are no longer enough to stay competitive in the job market.

Data Science 160

Data Science Machine Learning SQL Python 160

Data Engineering Podcast

JANUARY 5, 2020

Summary Databases are useful for inspecting the current state of your application, but inspecting the history of that data can get messy without a way to track changes as they happen. Debezium is an open source platform for reliable change data capture that you can use to build supplemental systems for everything from maintaining audit trails to real-time updates of your data warehouse.

Database 100

Database Kafka PostgreSQL MySQL 100

Teradata

JANUARY 8, 2020

Kevin Lewis offers his predictions for the data management and analytic trends that will accelerate in 2020. Read more!

Data Management 71

Data Management Management Data 71

Grouparoo

JANUARY 9, 2020

At Grouparoo , we have been interviewing a lot of marketers. The overall learning is that it's a hard job. The biggest reason is that they need data to make their campaigns work and do not have the means to get that data. Basically, they need Engineers to prioritize writing code to get the data into the tool they are using. That rarely happens.

Coding 52

Coding Project Engineering Building 52

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

Database

KDnuggets

JANUARY 7, 2020

Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.

Architecture 159

Architecture IT Process 159

Rockset

JANUARY 10, 2020

Performing ad-hoc analysis is a daily part of life for most data scientists and analysts on operations teams. They are often held back by not having direct and immediate access to their data because the data might not be in a data warehouse or it might be stored across multiple systems in different formats. This typically means that a data engineer will need to help develop pipelines and tables that can be accessed in order for the analysts to do their work.

Data Warehouse 40

Data Warehouse Data Pipeline Insurance Data Storage 40

KDnuggets

JANUARY 9, 2020

This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context.

Machine Learning 159

Machine Learning Algorithm Project Building 159

KDnuggets

JANUARY 7, 2020

An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.

Data Engineering 159

Data Engineering Data Engineer Engineering Big Data 159

KDnuggets

JANUARY 10, 2020

A resume plays a key role in bagging that dream data science job. We break down the nuances of a job-winning data science resume so that you can go ahead and transform your own resume.

Data Science 147

Data Science Data 147

KDnuggets

JANUARY 9, 2020

Data Scientists work with tons of data, and many times that data includes natural language text. This guide reviews 7 common techniques with code examples to introduce you the essentials of NLP, so you can begin performing analysis and building models from textual data.

Data 159

Data Coding Building Data Preparation 159

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Certification

KDnuggets

JANUARY 6, 2020

Reducing images to numbers makes them amenable to computation. Let's take a look at the why and the how using Python and Numpy.

Python 143

Python Process 143

KDnuggets

JANUARY 8, 2020

Check out this collection of 10 Python snippets that can be taken as a reference for your daily work.

Python 153

Python Programming 153

KDnuggets

JANUARY 10, 2020

Deepfakes have instilled panic in experts since they first emerged in 2017. Microsoft and Facebook have recently announced a contest to identify deepfakes more efficiently.

110

110

KDnuggets

JANUARY 4, 2020

Ethics in AI has received significant attention recently, and the new KDnuggets cartoon examines the problem of teaching ethics to artificially intelligent entities.

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115

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

JANUARY 9, 2020

Time series analysis will be the best tool for forecasting the trend or even future. The trend chart will provide adequate guidance for the investor. So let us understand this concept in great detail and use a machine learning technique to forecast stocks.

Machine Learning 112

Machine Learning Finance 112

KDnuggets

JANUARY 10, 2020

Finding a deep learning model to perform well is an exciting feat. But, might there be other -- less complex -- models that perform just as well for your application? A simple complexity measure based on the statistical physics concept of Cascading Periodic Spectral Ergodicity (cPSE) can help us be computationally efficient by considering the least complex during model selection.

Deep Learning 109

Deep Learning 109

KDnuggets

JANUARY 6, 2020

This article is an overview of H2O, a scalable and fast open-source platform for machine learning. We will apply it to perform classification tasks.

Machine Learning 149

Machine Learning IT Python 149

KDnuggets

JANUARY 8, 2020

Simply put: This post is about installing SQL, explaining SQL and running SQL.

SQL 130

SQL MySQL Programming 130

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

JANUARY 7, 2020

The healthcare AI market is expected to reach 28 billion dollars by the year 2025. With such exponential growth, AI is undoubtedly likely to bring some drastic changes in the healthcare industry. Let’s look at five ways of how AI has changed the healthcare industry.

Healthcare 79

Healthcare 79

KDnuggets

JANUARY 8, 2020

Introduction to Data Visualization & Storytelling;The Data Science Interview Study Guide; Why Kaggle will NOT make you a great Data Scientist; Cartoon: Teaching Ethics to AI.

Data Science 68

Data Science Data 68

KDnuggets

JANUARY 6, 2020

Breaking into a career in Data Science can depend on where you start. See if you fit into one of these three categories of "newbies," and then find out how to make your professional transition into the field.

Data Science 68

Data Science Data Software Engineer Software Engineering 68

KDnuggets

JANUARY 6, 2020

In this webinar, Jan 15 @ 12PM EST, we'll offer solutions to the common challenges data scientists and data engineers face when building a machine learning pipeline. Register now to attend live or to watch a recording afterwards.

Machine Learning 63

Machine Learning Building Data Engineering Data Engineer 63

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Project

KDnuggets

JANUARY 7, 2020

There is a need for a new way to explain complex, ensembled ML models for high-stakes applications such as credit and lending. This is why we invented GIG.

Machine Learning 76

Machine Learning 76

KDnuggets

JANUARY 9, 2020

Earn a Master of Professional Studies in Data Analytics online through Penn State World Campus – and you can add in-demand skills to your wheelhouse while you continue to work.

Data Science 60

Data Science Data Data Analytics Education 60

KDnuggets

JANUARY 7, 2020

Here are our top five hands-on training focus areas that every data scientist should know and that we’re paying extra attention to at ODSC East 2020 this April 13-17 in Boston.

Data 51

Data Data Science 51

KDnuggets

JANUARY 8, 2020

First issue of 2020 brings you a summary of how to "Ultralearn" Data Science - for those in a hurry; Explains how teams work on AutoML project; Why Python is a preferred language for Data Science; and a cartoon on teaching ethics to AI.

Data Science 50

Data Science Python Data Project 50

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

JANUARY 6, 2020

Also: Predict Electricity Consumption Using Time Series Analysis; What is the most important question for Data Science (and Digital Transformation); Why Python is One of the Most Preferred Languages for Data Science?; What is a Data Scientist Worth?; How to Speed up Pandas by 4x with one line of code.

Data Science 49

Data Science Machine Learning Project Python 49

KDnuggets

JANUARY 10, 2020

Also: Google's New Explainable AI Service; 10 Free Top Notch Machine Learning Courses.

Machine Learning 63

Machine Learning Data 63

Confluent

JANUARY 7, 2020

Following Google’s announcement to provide leading open source services with a cloud-native experience by partnering with companies like Confluent, we are delighted to share that Confluent Cloud is now available […].

Cloud 19

Cloud Kafka Programming 19