Rocket-Powered Data Science

DECEMBER 15, 2018

If we cannot know that ( i.e., because it truly is unsupervised learning), then we would like to know at least that our final model is optimal (in some way) in explaining the data. This challenge is known as the cold-start problem ! In those intermediate steps it serves as an evaluation (or validation) metric.

Machine Learning

Domino Data Lab

JULY 2, 2019

SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. AutoPandas: Origins.

Metadata

CIO Business Intelligence

DECEMBER 1, 2023

LexisNexis has been playing with BERT, a family of natural language processing (NLP) models, since Google introduced it in 2018, as well as Chat GPT since its inception. We will pick the optimal LLM. We’ll take the optimal model to answer the question that the customer asks.” But the foray isn’t entirely new.

Cost-Benefit

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. The TIOBE index confirms that the popularity of Python is increasing.

Data Science

Domino Data Lab

MARCH 16, 2021

2018) Simple meaningless data processing steps, may cause saliency methods to result in significant changes (Kindermans et al., Lately, however, there is very exciting research emerging around building concepts from first principles with the goal of optimizing the higher layers to be human-readable. Saliency Maps. Interpretable CNNs.

Modeling

datapine

NOVEMBER 19, 2019

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. Likewise, 2018 was the year of virtual assistants: Alexa, Cortana, all of them have taken the consumers’ market by storm.

Technology

Smart Data Collective

MAY 17, 2021

billion in 2018. It can also be used to analyze driver behaviors to optimize fuel stops, personal breaks and more. When it comes to fleet maintenance, big data can aid in monitoring vehicle handling and operation to optimize trips, preserve equipment and waylay potential breakdowns. Organizations have already realized this.

Big Data

CIO Business Intelligence

APRIL 25, 2023

A transformer is a type of AI deep learning model that was first introduced by Google in a research paper in 2017. ChatGPT was trained with 175 billion parameters; for comparison, GPT-2 was 1.5B (2019), Google’s LaMBDA was 137B (2021), and Google’s BERT was 0.3B (2018). What is ChatGPT? ChatGPT is a product of OpenAI.

Experimentation

CIO Business Intelligence

JULY 22, 2025

Legacy data center networking technologies just aren’t optimized to support the ultra-low latencies and high reliability and scalability to match unprecedented volumes of data, network responsiveness, and security demands of this AI era,” says Manish Gulyani , Nokia’s CMO for Network Infrastructure.

Machine Learning

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.

Risk

Domino Data Lab

SEPTEMBER 9, 2019

It’s important to note that machine learning for natural language got a big boost during the mid-2000’s as Google began to win international language translation competitions. The use cases for natural language have shifted dramatically over the past two years, after deep learning techniques arose to the fore.

Deep Learning

CIO Business Intelligence

MAY 30, 2024

Most recently, she has served as EVP and chief customer and technology officer at Ameren, which she joined 2018 as SVP and chief digital and information officer before adding customer experience and operations in 2023. It has been around since the 1950s with machine learning. However, this advancement doesn’t come without risks.

Data Quality

CIO Business Intelligence

APRIL 11, 2022

That wasn’t a fluke either, as the 2019 numbers were four times higher than 2018. To create a productive, cost-effective analytics strategy that gets results, you need high performance hardware that’s optimized to work with the software you use. Just starting out with analytics?

Deep Learning

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). The data types used in deep learning are interesting. The data types used in deep learning are interesting. One-fifth use reinforcement learning.

Data Science

Domino Data Lab

FEBRUARY 10, 2019

Humans likely not even notice the difference but modern deep learning networks suffered a lot. But apparently, models trained on text from 2017 experience degraded performance on text written in 2018. Machine Learning requires lots and lots of relevant training data. We might expect that.

Machine Learning

IBM Big Data Hub

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. An open-source model, Google created BERT in 2018.

Modeling

Insight

JANUARY 14, 2020

Lauren Holzbauer was an Insight Fellow in Summer 2018. Keras is an open source deep learning API that was written in Python and runs on top of Tensorflow, so it’s a little more user-friendly and high-level than Tensorflow. We pass 3 parameters: loss, optimizer , and metrics. Check out the Keras documentation here.

Metrics

Cloudera

SEPTEMBER 12, 2018

. — Mike Barlow, author of “Learning to Love Data Science” (O’Reilly Media). And now, without further delay, we are excited to announce the winners of the 2018 Data Impact Awards, listed by award theme and category: Business Impact. Two weeks ago, we announced the finalists.

Machine Learning

Insight

MARCH 28, 2019

For the Fall 2018 session of the Insight Fellows Program in NYC, we launched a new partnership with Thinknum , a company that provides alternative data indexed from the web to institutional investors and corporations? Utilize information hidden away in online employee reviews. Yanxia Li earned her Ph.D.

Dashboards

CIO Business Intelligence

JULY 25, 2024

Emphasizing data-driven decision-making in Aurora In 2018, the City of Aurora, Ill., The city hopes AI tools will help streamline administrative processes, automate routine tasks, and optimize resource allocation. Prototyping the smart San Antonio of the future In 2023, the City of San Antonio launched its Smarter Together initiative.

IT

Domino Data Lab

MAY 8, 2019

2018-06-21). For example, in the case of more recent deep learning work, a complete explanation might be possible: it might also entail an incomprehensible number of parameters. Perhaps if machine learning were solely being used to optimize advertising or ecommerce, then Agile-ish notions could serve well enough.

Machine Learning

Domino Data Lab

JULY 22, 2019

and drop your deep learning model resource footprint by 5-6 orders of magnitude and run it on devices that don’t even have batteries. The year 2018 was what Wall Street Journal called “ a global reckoning on data governance.” Machine learning is a subset of mathematical optimization.

Data Science

Insight

MARCH 5, 2019

As machine learning (ML) algorithms increase in popularity and the “black boxes” of neural networks in deep learning (DL) become the industry standard, pulling out the demographic information and the user history responsible for each undesired rec becomes next to impossible to achieve.

Machine Learning

O'Reilly on Data

SEPTEMBER 11, 2019

So, we used a form of the Term Frequency-Inverse Document Frequency (TF/IDF) technique to identify and rank the top terms in this year’s Strata NY proposal topics—as well as those for 2018, 2017, and 2016. 2) is unchanged from Strata NY 2018, it’s up three places from Strata NY 2017—and eight places relative to 2016. 221) to 2019 (No.

IoT