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? Checkout: Reltio Careers. #5

Statistics 110

Statistics Data Science Machine Learning Software 110

KDnuggets

AUGUST 21, 2019

This week's news: Become More Marketable as a Data Scientist; Command Line Basics Every Data Scientist Should Know; Chatbots with Keras!; Understanding Cancer using Machine Learning; Statistical Modelling vs Machine Learning; Is Kaggle Learn a "Faster Data Science Education?";

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Rocket-Powered Data Science

MARCH 10, 2020

In 2019, I was asked to write the Foreword for the book “ Graph Algorithms: Practical Examples in Apache Spark and Neo4j “ , by Mark Needham and Amy E. I wrote an extensive piece on the power of graph databases, linked data, graph algorithms, and various significant graph analytics applications.

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KDnuggets

SEPTEMBER 17, 2019

We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.

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Business Over Broadway

MAY 22, 2019

Also, loyalty leaders infuse analytics into CX programs, including machine learning, data science and data integration. How employees can drive transformation and emerging technology adoption: Both are data-heavy endeavors; We know that statistics/math knowledge is related to data science project success.

Machine Learning 40

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DataRobot

AUGUST 5, 2021

In 2019, Utah struck a deal with Banjo, a threat detection firm selling AI services to process live traffic feeds, dispatch logs, and other data. After making their first estimate, all participants were shown rental price predictions from a machine learning model. Is there too much hype about AI or too much doomsaying?

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FineReport

DECEMBER 19, 2019

If you want to learn more about self-service BI tools, you can take a look at this review: 5 Most Popular Business Intelligence (BI) Tools in 2019 , to understand your own needs and then choose the tool that is right for you. Pandas is a Python data science library that is constantly improving.

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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. Growth is still strong for such a large topic, but usage slowed in 2018 (+13%) and cooled significantly in 2019, growing by just 7%.

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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 one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

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Machine Learning Deep Learning Modeling Interactive 108

KDnuggets

OCTOBER 31, 2019

These results will go into each each region and employment type to find out the differences and similarities especially between people from Industry and Students.

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Sisense

DECEMBER 3, 2019

In order to empower the world’s business, data, and product teams to drive digital transformation, we recently announced two major leaps forward for the Sisense Platform. With a single click, an ensemble of univariate forecast models run against your data. An AI algorithm selects the best model based on the type of data analyzed.

Data Warehouse 90

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Business Over Broadway

JANUARY 19, 2021

Nearly half of data professionals surveyed in Kaggle’s 2020 Data Science and Machine Learning Survey said they do not use BI tools. The top tool used by data professionals to analyze data are local development environments (48%), followed by basic statistical software (30%).

Business Intelligence 85

Business Intelligence Analytics Statistics Machine Learning 85

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. Sci Foo 2019.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Business Over Broadway

JULY 29, 2020

Analysis of usage of 5 primary tools used to analyze data showed that the top tool used by data professionals to analyze data are local development environments (54%), followed by basic statistical software (20%), cloud-based data software and APIs (8%), advanced statistical software (6%) and business intelligence software (6%).

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The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. In conferences and research publications, there is a lot of excitement these days about machine learning methods and forecast automation that can scale across many time series.

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Domino Data Lab

MAY 8, 2019

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Machine learning model interpretability.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks. Data poisoning attacks. General concerns.

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Business Over Broadway

JULY 14, 2020

Kaggle conducted a worldwide survey in October 2019 of 19,717 data professionals ( 2019 Kaggle Machine Learning and Data Science Survey ). Their survey included a variety of questions about data science, tool usage, machine learning, education and more.

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The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. e-handbook of statistical methods: Summary tables of useful fractional factorial designs , 2018 [3] Ulrike Groemping. Hedayat, N.J.A.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Smart Data Collective

OCTOBER 14, 2019

Regardless of if you’re a data science professional or an IT department who wants to help your company have more successful data science projects, it’s essential to have some data science tools under your belt to avail of when needed. Here are some open-source options to consider. Apache Drill.

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Data Science Machine Learning Big Data Interactive 68

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! After a data science conference, our marketing group wanted to follow-up by surveying 300 attendees from industry.

Data Science 49

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Insight

FEBRUARY 19, 2020

Using variability in machine learning predictions as a proxy for risk can help studio executives and producers decide whether or not to green light a film project Photo by Kyle Smith on Unsplash Originally posted on Toward Data Science. In 2019, Netflix alone released 371 new TV shows and movies.

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O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. Use ML to unlock new data types—e.g.,

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Smarten

NOVEMBER 18, 2022

Research reveals that the global statistical natural language processing (NLP) market size is projected to grow to $3.7 Natural Language processing-based search capability allows business users with average technical skills to gather and analyze data without the need to scroll through menus or write complex queries.

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O'Reilly on Data

JANUARY 25, 2021

Year-over-year (YOY) growth compares January through September 2020 with the same months of 2019. Let’s look at the data, starting at the highest level: O’Reilly online learning itself. O’Reilly Online Learning. Usage of O’Reilly online learning grew steadily in 2020, with 24% growth since 2019.

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datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. 2019 was a particularly major year for the business intelligence industry. Suddenly advanced analytics wasn’t just for the analysts.

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datapine

DECEMBER 4, 2019

Applied to business, it is used to analyze current and historical data in order to better understand customers, products, and partners and to identify potential risks and opportunities for a company. The accuracy of the predictions depends on the data used to create the model. Mobile Analytics.

Business Intelligence 212

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Andrew White

JANUARY 11, 2021

As such a head of analytics, BI and data science may emerge. Are you anticipating continued separation of “BI/Analytics” teams from “Data Science” teams or are those roles merging in the years ahead? Many data science labs are set up as shared services. That’s the idea.

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