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. In isolation, the $x_1$-system is optimal: changing $x_1$ and leaving the $x_2$ at 0 will decrease system performance.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

datapine

SEPTEMBER 27, 2022

Originally published in 2018, the book has a second edition that was released in January of 2022. 14) “High-Performance MySQL: Optimization, Backups, and Replication” by Baron Schwartz, Peter Zaitsev, and Vladimir Tkachenko. 4) “SQL Performance Explained” by Markus Winand. Would highly recommend for SQL experts.”.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

O'Reilly on Data

FEBRUARY 18, 2020

Growth is still strong for such a large topic, but usage slowed in 2018 (+13%) and cooled significantly in 2019, growing by just 7%. But sustained interest in cloud migrations—usage was up almost 10% in 2019, on top of 30% in 2018—gets at another important emerging trend. ML + AI are up, but passions have cooled. Security is surging.

Data-driven 344

Data-driven Software Statistics Marketing 344

Smart Data Collective

DECEMBER 18, 2020

Hackers have turned to exploiting website optimization platform Google Analytics to steal credit cards, passwords, IP addresses and a whole host of compromising information that can be shared by hacked sites. Image: Infosec ).

Analytics 86

Analytics Broadcasting Measurement Data Processing 86

Business Over Broadway

MAY 22, 2019

For those of you who are interested, here is Gartner’s latest (2018) hype cycle on emerging technologies. 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. So, become data literate.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

Occam's Razor

JULY 24, 2018

The ability to optimize landing pages. At the top-right, you’ll discover my obsession with Profit and Incrementality, which form the basis of competitive advantage in 2018 (and beyond). So, how do we ensure that each has an optimal analytical approach? Is the distribution optimal? What do you see?

Analytics 95

Analytics Metrics Strategy Measurement 95

O'Reilly on Data

NOVEMBER 28, 2023

ChatGPT has driven a focus on personal use cases, but there are many applications where problems of bias and fairness aren’t major issues: for example, examining images to tell whether crops are diseased or optimizing a building’s heating and air conditioning for maximum efficiency while maintaining comfort.

Enterprise 280

Enterprise Modeling Testing Reporting 280

CDW Research Hub

JUNE 5, 2019

Varonis compiled 60 cybersecurity statistics to give you a better idea of the current cybersecurity state, and we’ve broken out five key facts to help you rethink your data security program. Check out Varonis’ full list of 60 Must-Know Cybersecurity Statistics for 2019. Show Me the Money. clocking in 126, according to Global Finance.

Statistics 72

Statistics Risk Management Finance Risk 72

Cloudera

DECEMBER 15, 2020

Those were documented in early 2018 in this blog from a mixed Intel and Baidu team. Catalyst now stops at each stage boundary to try and apply additional optimizations given the information available on the intermediate data. Dynamically Optimize Skewed Joins. One of most awaited features of Spark 3.0 When both .

Broadcasting 101

Broadcasting Optimization Statistics IT 101

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. The year 2018 was what Wall Street Journal called “ a global reckoning on data governance.” Tukey did this paper.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

CIO Business Intelligence

AUGUST 21, 2024

Starting in 2018, the agency used agents, in the form of Raspberry PI computers running biologically-inspired neural networks and time series models, as the foundation of a cooperative network of sensors. These projects include those that simplify customer service and optimize employee workflows. It’s a system still being used today.

Risk 135

Risk Insurance Cost-Benefit Software 135

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. With those stakes and the long forecast horizon, we do not rely on a single statistical model based on historical trends. Our team does a lot of forecasting.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

datapine

NOVEMBER 19, 2019

Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI. There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others.

Technology 279

Technology Internet of Things IT IoT 279

Smarten

SEPTEMBER 6, 2019

In the meantime, business users have a tool that is sophisticated enough to present clear, accurate, measurable results and allow them to find the source of problems, optimize results and share data to support business decisions.

Analytics 53

Analytics IT Business Intelligence Testing 53

Domino Data Lab

MAY 8, 2019

2018-06-21). They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Perhaps if machine learning were solely being used to optimize advertising or ecommerce, then Agile-ish notions could serve well enough. Challenges for Transparency ”.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). By mid-2018, use of AutoML had captured little interest in enterprise—only a single digit percentage among our respondents for the first survey. Spark, Kafka, TensorFlow, Snowflake, etc.,

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] You can home in on an optimal value by specifying, say, 32 dimensions and varying this value by powers of 2. If we were using CBOW, then a window size of 5 (for a total of 10 context words) could be near the optimal value. Example 11.6

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

O'Reilly on Data

MAY 21, 2019

For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production. Another algorithm (the “trainer” and “pipeline”) that uses data to produce the Model that best optimizes some objective function.

Machine Learning 246

Machine Learning Technology Deep Learning Data Science 246

datapine

NOVEMBER 27, 2019

The demand for real-time online data analysis tools is increasing and the arrival of the IoT (Internet of Things) is also bringing an uncountable amount of data, which will promote the statistical analysis and management at the top of the priorities list. BN in 2018, it is also predicted to grow with a CAGR rate of 22.43% by reaching 2024.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361