O'Reilly on Data

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Up until 2017, the ML+AI topic had been amongst the fastest growing topics on the platform. Coincidence? Probably not, but only time will tell.

Data-driven 363

Data-driven Software Statistics Marketing 363

Data Science 101

APRIL 26, 2019

While it is not one of the popular programming languages for data science, The Go Programming Language (aka Golang) has surfaced for me a few times in the past few years as an option for data science. I decided to do some searching and find some conclusions about whether golang is a good choice for data science.

Data Science 111

Data Science Machine Learning Interactive Risk 111

Analytics Vidhya

OCTOBER 1, 2022

This article was published as a part of the Data Science Blogathon. Introduction In 2017, The Economist declared that “the world’s most valuable resource is no longer oil, but data.” Companies like Google, Amazon, and Microsoft gather large bytes of data, harvest it, and create complex tracking algorithms.

Data-driven 270

Data-driven Data Science Publishing Analytics 270

Business Over Broadway

MARCH 8, 2021

Results of a survey of data professionals show that about 1 out of 5 are women. Ways of improving gender diversity in the field of data science are offered. How does gender diversity look in the data science world? Annual Salaries of Data Professionals from the US. Click image to enlarge.

Data Science 138

Data Science Machine Learning Statistics Reporting 138

Business Over Broadway

DECEMBER 20, 2018

The importance of data science and machine learning continues to grow in business and beyond. I did my part this year to spread interest in data science to more people. Below are my top 10 blog posts of 2018: Favorite Data Science Blogs, Podcasts and Newsletters. Click image to enlarge.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74

Business Over Broadway

JANUARY 27, 2019

The most popular ML frameworks include Scikit-Learn, Tensorflow and Keras. Machine Learning Frameworks used in last 5 years. The practice of data science requires the use of machine learning products and frameworks to help data professionals automate processes that drive their business forward.

Machine Learning 89

Machine Learning Data Science Technology Analytics 89

Smart Data Collective

SEPTEMBER 17, 2019

Machine learning is creating pivotal change in the energy industry. Towards Data Science wrote about the changes that machine learning is bringing to this field. You need to consider the benefits of using an electrical system that relies on machine learning technology.

Machine Learning 90

Machine Learning Enterprise Insurance Cost-Benefit 90

IBM Big Data Hub

DECEMBER 4, 2017

Readers of the IBM Big Data & Analytics Hub were hungry for knowledge this year. They voraciously read blog posts about incorporating machine learning, choosing the best possible data model, determining how to make the most of data science skills, working with open source frameworks and more.

Big Data 77

Big Data Data Analytics Analytics Machine Learning 77

Business Over Broadway

JANUARY 13, 2019

The practice of data science requires the use of analytics tools, technologies and programming languages to help data professionals extract insights and value from data. A recent survey of nearly 24,000 data professionals by Kaggle revealed that Python, SQL and R are the most popular programming languages.

Machine Learning 110

Machine Learning Data Science Visualization Technology 110

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. On the one hand, basic statistical models (e.g.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

Smart Data Collective

APRIL 5, 2022

The data science profession has become highly complex in recent years. Data science companies are taking new initiatives to streamline many of their core functions and minimize some of the more common issues that they face. IBM Watson Studio is a very popular solution for handling machine learning and data science tasks.

Machine Learning 145

Machine Learning Cost-Benefit Data Science Unstructured Data 145

Business Over Broadway

JUNE 29, 2020

The practice of data science, including work in machine learning and artificial intelligence, requires the use of analytics tools, technologies and programming languages. A recent survey of nearly 20,000 data professionals by Kaggle revealed that Python, SQL and R continue to be the most popular programming languages.

Machine Learning 128

Machine Learning Data Science Technology Analytics 128

David Menninger's Analyst Perspectives

OCTOBER 5, 2018

In 2017 Strata + Hadoop World was changed to the Strata Data Conference. As I pointed out in my coverage of last year’s event , the focus was largely on machine learning and artificial intelligence (AI).

Marketing 140

Marketing Machine Learning Technology Management 140

datapine

NOVEMBER 27, 2019

Often seen as the highest foe-friend of the human race in movies ( Skynet in Terminator, The Machines of Matrix or the Master Control Program of Tron), AI is not yet on the verge to destroy us, in spite the legit warnings of some reputed scientists and tech-entrepreneurs. 1 for data analytics trends in 2020.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Data Science 101

APRIL 12, 2019

LinkedIn’s 2017 report had put Data Scientist as the second fastest growing profession and it’s number one on 2019’s list of most promising jobs. There are three main reasons why data science has been rated as a top job according to research. How can you get a job as a data scientist?

Statistics 110

Statistics Data Science Machine Learning Software 110

Cloudera

JANUARY 19, 2018

Before we get too far into 2018, let’s take a look at the ten most popular Cloudera VISION blogs from 2017. On April 28, 2017, Mike Olson , as one of the founders of Cloudera, writes about the initial public offering, and what the milestone means. “We Machine Learning in the Age of Big Data. Fast Forward!

Machine Learning 45

Machine Learning Big Data Data Science IoT 45

Domino Data Lab

FEBRUARY 10, 2019

This blog post provides insights into why machine learning teams have challenges with managing machine learning projects. Why are Machine Learning Projects so Hard to Manage? I’ve watched lots of companies attempt to deploy machine learning?—?some Why is this? We might expect that.

Machine Learning 63

Machine Learning Modeling Deep Learning Metrics 63

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Doesn’t this seem like a worthy goal for machine learning—to make the machines learn to work more effectively?

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Metadata Data Science Machine Learning Data-driven 105

Cloudera

FEBRUARY 16, 2018

In many ways, 2017 was a singular year for Cloudera, not least because we staged a successful IPO and joined the ranks of the world’s fastest-growing, publicly traded companies. Winner of Datanami Reader’s Choice award for Best Data Science Platform. UK’s V3 Technology Award as best AI/Machine Learning Provider.

IoT 45

IoT Machine Learning Manufacturing Data Science 45

Insight

MARCH 29, 2019

Over the last three years, I’ve worked with more than 500 Insight Fellows , coaching them as they transition to thriving industry careers in data science, data engineering, and artificial intelligence. However, even as she enthusiastically interviewed for the role of VP and Head of Data Science at Dotdash?—?a

Data Science 73

Data Science Management ROI Data Processing 73

CIO Business Intelligence

APRIL 15, 2022

In 2017, The Economist declared that data, rather than oil, had become the world’s most valuable resource. Organizations across every industry have been and continue to invest heavily in data and analytics. But like oil, data and analytics have their dark side. The refrain has been repeated ever since.

Analytics 145

Analytics Machine Learning Insurance Testing 145

CIO Business Intelligence

MARCH 25, 2022

I bring the tech and cyber expertise to those boards, and also the digital piece,” adds Martin, a member of the CIO Hall of Fame since 2017. “It It’s part of everything you hear about—the use of data, automation and robotics—helping to drive the operational strategy and new ways to improve efficiencies or reduce waste.

Digital Transformation 115

Digital Transformation Machine Learning Uncertainty Strategy 115

CIO Business Intelligence

AUGUST 11, 2023

How natural language processing works NLP leverages machine learning (ML) algorithms trained on unstructured data, typically text, to analyze how elements of human language are structured together to impart meaning. Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining.

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Unstructured Data Machine Learning Data Science Data mining 142

Domino Data Lab

MAY 20, 2021

Machine Learning algorithms often need to handle highly-imbalanced datasets. note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). A weighted nearest neighbor algorithm for learning with symbolic features. Machine Learning, 57–78.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Domino Data Lab

SEPTEMBER 18, 2019

This post covers data exploration using machine learning and interactive plotting. Models are at the heart of data science. Data exploration is vital to model development and is particularly important at the start of any data science project. Introduction. Chapter Introduction: Real Estate.

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Visualization Interactive Machine Learning Data Science 99

DataRobot Blog

OCTOBER 3, 2017

A Director of Information Analytics Services at a large, multinational healthcare services company is responsible for collecting and changing data schematics from third-party sources, matching and integrating mixed profiles of users, and mapping it to a conformed format. DataRobot Data Prep. free trial. Try now for free.

Data Lake 52

Data Lake Data Architecture Advertising Insurance 52

O'Reilly on Data

JANUARY 22, 2019

They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. Whether financial models are based on academic theories or empirical data mining strategies, they are all subject to the trinity of modeling errors explained below.

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Modeling Finance Uncertainty Data mining 212

Smart Data Collective

MARCH 23, 2022

However, we have witnessed a significant uptick in ADA cases being filed against website owners since 2017. Evan Morris of Towards Data Science discussed this in one of his recent articles. between Q1 of 2017 and Q1 of 2018. Use a machine learning tool to automate compliance. That’s a lot of cash!

Cost-Benefit 128

Cost-Benefit Data mining Sales Testing 128

Business Over Broadway

JANUARY 11, 2021

Data professionals of all stripes, including data scientists, machine learning engineers and others, use different types of tools in their jobs. A recent survey of over 20,000 data professionals by Kaggle revealed that Python, SQL and R continue to be the most popular programming languages. Click image to enlarge.

Machine Learning 56

Machine Learning Data Science Software IT 56

Data Science 101

MAY 6, 2019

So it was a natural transition for me to move to a career that felt like it had higher impact, a wide variety of work, and good career opportunity—and data science was that was that move for me. We pulled questions from some of our Springboard students and this one is from Miguel, who is in our data science vertical.

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Data Science Machine Learning Modeling Testing 98

Insight

AUGUST 29, 2019

Insight Boston began its journey in 2015, with the first and only fellowship program dedicated to a career in Health Data Science. In 2017, we expanded the location to include our Data Science program, and in early 2018, we welcomed our first Data Engineering Fellows.

Data Science 56

Data Science Machine Learning Sales Measurement 56

Jedox

JULY 17, 2018

Many of us already profit from machine learning or artificial intelligence – often without even thinking about it. Finance in its new role, sitting at the center of data analytics, is increasingly expected to deliver the data-driven insights to guide company strategy.

Machine Learning 47

Machine Learning Technology Digital Transformation Predictive Analytics 47

Domino Data Lab

SEPTEMBER 9, 2019

Data science teams in industry must work with lots of text, one of the top four categories of data used in machine learning. That’s excellent for supporting really interesting workflow integrations in data science work. Usually it’s human-generated text, but not always.

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Smart Data Collective

JUNE 10, 2019

Python is one of the most important languages for data science. You will encounter it all over web applications, network servers, desktop application, media tools, machine learning, and others. Back in 2017, Google declared Kotlin to be the official Android Development Language.

IoT 105

IoT Machine Learning Interactive Data Science 105

Domino Data Lab

APRIL 3, 2019

The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Rinse, lather, repeat.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

Cloudera

SEPTEMBER 10, 2021

Key to harnessing the power of all that data: high-powered artificial intelligence tools, machine learning capabilities and applications capable of rapidly exposing attempts at fraud or identity theft. We need to be able to make accurate decisions at speed while utilizing vast swathes of data.

Machine Learning 69

Machine Learning Statistics Data-driven Big Data 69