datapine

AUGUST 29, 2022

Best for : the new intern who has no idea what data science even means. An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

DataRobot

MAY 11, 2021

It 10x’s our world-class AI platform by dramatically increasing the flexibility of DataRobot for data scientists who love to code and share their expertise across teams of all skill levels. At DataRobot, we have always known that data science is a team sport. Customize and automate your data science workflows.

Data Science 98

Data Science Cost-Benefit Data Processing Modeling 98

Domino Data Lab

AUGUST 1, 2021

2016) for an example of this technique (LIME). Notice that the PDP generation and inspection acts globally – this approach considers all data samples and provides insights on the relationship between the selected independent variables and the target given the dataset as a whole. 1135–1144, ACM, 2016. See Ribeiro et al.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Alation

DECEMBER 15, 2022

March 2015: Alation emerges from stealth mode to launch the first official data catalog to empower people in enterprises to easily find, understand, govern and use data for informed decision making that supports the business. April 2016: Tesco Group becomes first customer outside North America.

Metadata 52

Metadata Data Governance Data Quality Marketing 52

DataRobot Blog

JUNE 11, 2018

IBM Watson Studio has come a long way since I first tested IBM Data Science Experience in November 2016. The new Watson Studio delivers a more collaborative, enterprise quality data. by Jen Underwood. Read More.

Data Science 40

Data Science Testing Enterprise Predictive Analytics 40

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

CIO Business Intelligence

OCTOBER 4, 2023

From 2016 to 2022, the company went from processing a payments volume of $354 billion to $1.36 One strategy, five keys From a technological point of view, the brand’s strategic engine is divided into five investment areas. This allows us greater productivity and creativity on the part of developers,” he says. trillion last year.

Digital Transformation 124

Digital Transformation Deep Learning Data Lake Risk 124

Andrew White

JANUARY 9, 2020

Examples are given: one is a Chinese firm who apparently has 300,000 staff tagging data every minute of every day – to feed into its ML technologies to drive more effective AI solutions. But then I remembered synthetic data. So I wonder – when will synthetic data be (yet another) next big thing?

Machine Learning 59

Machine Learning Data Science Technology IT 59

Cloudera

SEPTEMBER 24, 2021

As data volumes soared – particularly with the rise of smartphones – appliance based models became eye-wateringly expensive and inflexible. They were using R and Python, with NoSQL and other open source ad hoc data stores, running on small dedicated servers and occasionally for small jobs in the public cloud.

Analytics 91

Analytics IoT Cost-Benefit Big Data 91

Data Science and Beyond

JULY 28, 2017

Ideally, I wanted a well-paid data science-y remote job with an established distributed tech company that offers a good life balance and makes products I care about. While data wrangler may sound less sexy than data scientist , reading the job ad led me to believe that the position may involve interesting data science work.

Data Science 81

Data Science Testing Measurement Uncertainty 81

CIO Business Intelligence

MARCH 25, 2022

With all the focus today on this transformation work, boards must ensure that no organization falls behind on the business benefits to be gained by leveraging technologies in data science, AI, machine learning, blockchain, etc. You joined your first public board in 2017, while still working fulltime as CIO at Baxter International.

Digital Transformation 103

Digital Transformation Uncertainty Machine Learning Strategy 103

CIO Business Intelligence

MAY 17, 2022

Microsoft’s Tay chatbot, released on Twitter in 2016, quickly started spewing racist, misogynist, and anti-Semitic messages. This particular hospital’s data science team had built a system to identify such comorbidities. The hospital did this by investing more in data collection, Taglieti says. Can we automate?”.

Risk 142

Risk Consulting Machine Learning Data Science 142

Smart Data Collective

JULY 16, 2023

For example, due to computerization and algorithmic trading, Goldman Sachs decreased the number of people trading stocks from 600 to 2, from 2000 to 2016. By analyzing vast amounts of data, we unveil patterns and correlations that were previously hidden. The law of big numbers reinforces the reliability and accuracy of our analyses.

Big Data 77

Big Data Marketing Strategy Insurance 77

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

Rita Sallam

JULY 31, 2017

Furthermore, data science modeling, which is also largely manual, requires specialist skills that are in short supply at time when insights from advanced analytics must be pervasive to fuel digital business transformation. It will transform how users interact with data, and how they consume and act on insights.

Marketing 72

Marketing Analytics Machine Learning Data Science 72

Andrew White

JUNE 3, 2022

One of blogs in 2016 teed up some ideas I was working on at the time: Where You Spend Your Firms’ Capital Matters. In modern parlance, why would invest in new analytics, data science or AI technologies but also, always, upgrade our data literacy, management, organization and people skills? Studies continue.

ROI 52

ROI Publishing Analytics Data Science 52

Smarten

JANUARY 3, 2019

The Gartner report entitled, ‘ Citizen Data Science Augments Data Discovery and Simplifies Data Science,’ dated December 9, 2016 (ID G00314599) states that, ‘ Through 2017, the number of citizen data scientists will grow five times faster than the number of highly skilled data scientists.’

Business Intelligence 40

Business Intelligence Statistics Interactive Reporting 40

Cloudera

SEPTEMBER 28, 2020

ACID transactions, ANSI 2016 SQL SupportMajor Performance improvements. The data lifecycle model ingests data using Kafka, enriches that data with Spark-based batch process, performs deep data analytics using Hive and Impala, and finally uses that data for data science using Cloudera Data Science Workbench to get deep insights.

Testing 131

Testing Metadata Risk Data Science 131

Insight

AUGUST 8, 2019

Whether they’re looking to transition to Data Science, Health Data Science, Data Engineering, Artificial Intelligence, DevOps Engineering, Decentralized Consensus, or Security, Insight Fellows typically already have 90% of the skills they need to succeed in the field. Insight’s model is very different from this.

Data Science 66

Data Science Cost-Benefit Big Data Management 66

Jen Stirrup

JUNE 20, 2020

In efficient data science, we need to take our biases off the table in order to get a true picture of the data we are looking at. Here is the Current Ratio for the past four years for PASS: Year 2019 2018 2017 2016 Quick Ratio ((Current Assets) / Current Liabilities ) 1.03 Let’s see that data for the past few years.

Metrics 104

Metrics Business Analytics Data-driven Statistics 104

Domino Data Lab

JULY 1, 2021

This combination of CRF and BiLSTM is often referred to as a BiLSTM-CRF model (Lample et al 2016), and its architecture is shown in Figure 2. Data exploration and preparation. We start by importing all the libraries needed for the ingestion, exploratory data analysis, and model building. import pickle import operator.

Modeling 111

Modeling Statistics Testing Metrics 111

Rita Sallam

SEPTEMBER 11, 2020

In 2016, life expectancy in the United States (78.5) The United States grew the least at only 2% from 2000 to 2016. Don’t miss the Data Science and Machine Learning Bake-Off on September 15th at 1:pm EDT. was almost 4yrs less than the average of all other countries combined (82).

Statistics 96

Statistics Machine Learning Sales Data Science 96

Sanjeev Mohan

FEBRUARY 6, 2019

My journey in helping our customers with their technical queries started when I joined Gartner in late 2016. I spent the majority of my time helping clients decide which was the right Hadoop platform and which NoSQL / nonrelational data store to pick for specific use cases. So, why did I decide to write on this topic?

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

DataRobot Blog

MARCH 10, 2022

The “Fourth Industrial Revolution” was coined by Klaus Schwab of the World Economic Forum in 2016. Python is unarguably the most broadly used programming language throughout the data science community. After a model has been selected for production, most data science teams are faced with the question of “now what?”

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

Domino Data Lab

JANUARY 6, 2019

In Paco Nathan ‘s latest column, he explores the theme of “learning data science” by diving into education programs, learning materials, educational approaches, as well as perceptions about education. He is also the Co-Chair of the upcoming Data Science Leaders Summit, Rev. Learning Data Science.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

DataRobot Blog

AUGUST 23, 2019

Fans of betting and data science are excited to see how predictive the 100,000 simulations turn out to be, fed by ATP and WTA matches over nine seasons with Elo scores, and factoring in surface and more. The post 2019 US Open Predictions: Doubling Down on the Data appeared first on DataRobot AI Cloud. Andrew received his Ph.D.

Predictive Modeling 52

Predictive Modeling Modeling Marketing Analytics Data Science 52

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. Introduction Time series data appear in a surprising number of applications, ranging from business, to the physical and social sciences, to health, medicine, and engineering.

Forecasting 64

Forecasting Statistics Modeling Software 64

Smarten

JUNE 15, 2022

Ask a question about a point in time without the need for specific dates: How many silk blouses were sold during Christmas season in 2016 vs. 2018? Ask a question that reveals ‘most’ or ‘least’, ‘high’ or ‘low’: What was the highest temperature in Arizona in 2019 and when did it happen?

Analytics 52

Analytics ROI Data-driven Sales 52

Occam's Razor

MARCH 30, 2017

While the phrase Artificial Intelligence has been around since the first human wondered if she could go further if she had access to entities with inorganic intelligence, it truly jumped the shark in 2016. trillion pictures in 2016. One key thing that stymied my efforts, and likely your ML efforts, in 2016 was Identity.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Domino Data Lab

SEPTEMBER 25, 2019

Conducting exploratory analysis and extracting meaningful insights from data are core components of research and data science work. Time series data is commonly encountered. We see it when working with log data, financial data, transactional data, and when measuring anything in a real engineering system. . >

Forecasting 87

Forecasting Modeling Statistics Optimization 87

Insight

MARCH 18, 2019

As data scientists, machine learning engineers, and AI practitioners, we should be aware of the behaviors of the models we build and check them for biases toward certain attributes, such as race or sex. Want to advance your career in Data Science and Artificial Intelligence? Feel free to get in touch.

Machine Learning 77

Machine Learning Predictive Modeling Modeling Metrics 77

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

GAMs are popular among data science and machine learning applications for their simplicity and interpretability. For example, one could apply logarithms or add polynomial terms for certain features. A more general approach is to learn a Generalized Additive Model (GAM). Pfeifer, J., Voevodski, K., Mangylov, A., Moczydlowski, W.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

The Unofficial Google Data Science Blog

APRIL 23, 2024

17:263-287, 2016. [10] Journal of Machine Learning Research, 17(83):1–5, 2016. [23] G - Reference, Information and Interdisciplinary Subjects Series, Harvard Business Review Press, 2015. [9] 9] Thomas Lipp and Stephen P. Variations and extension of the convex–concave procedure. Optimization and Engineering., Domahidi, E. Chu, and S.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Andrew White

JANUARY 9, 2022

This research does not tell you where to do the work; it is meant to provide the questions to ask in order to work out where to target the work, spanning reporting/analytics (classic), advanced analytics and data science (lab), data management and infrastructure, and D&A governance. We write about data and analytics.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Domino Data Lab

OCTOBER 23, 2019

Eighty percent of this problem is collecting the data and then transforming the data. The other 20 percent is ML- and data science–related tasks like finding the right model, doing EDA, and feature engineering. Gathering the Data. there is a list of data sources to extract and transform. In Figure 6.1,

Statistics 59

Statistics Machine Learning Testing Modeling 59

Insight

JUNE 10, 2019

In 2016, Uber published its Uber Elevate White Paper , setting its aspirations on providing on-demand air taxis from San Francisco to San Jose for about $130. Alexander | June 1, 2016 Training a c onvolution neural network (CNN) to spot helipads The solution I developed rests on retraining a CNN to recognize helipads in aerial images.

Breakeven 69

Breakeven Modeling Testing Marketing 69

The Unofficial Google Data Science Blog

MARCH 13, 2017

By MUKUND SUNDARARAJAN, ANKUR TALY, QIQI YAN Editor's note: Causal inference is central to answering questions in science, engineering and business and hence the topic has received particular attention on this blog. CoRR, 2016. [3] CoRR, 2014. [2] 2] Shrikumar, Avanti, Greenside, Peyton, Shcherbina, Anna, and Kundaje, Anshul.

IT 68

IT Visualization Modeling Uncertainty 68