KDnuggets

JANUARY 18, 2023

Can ChatGPT provide answers to data science questions to the same standard of humans? Check out this attempt to do so, and compare the answers to those from experts.

Data Science 146

Data Science Data 146

Teradata

JANUARY 18, 2023

GxPs are a set of guidelines used to reduce risk when dealing with tech suppliers. But guidelines are not certification tests. Learn what to consider when assessing reliability in the cloud.

Cloud 64

Cloud Certification 64

KDnuggets

JANUARY 18, 2023

We will be learning web scraping and training supervised machine-learning algorithms to predict winning teams.

Machine Learning 146

Machine Learning Python Algorithm 146

AltexSoft

JANUARY 18, 2023

In 2020, a remarkable AI took Silicon Valley by storm. Dubbed GPT-3 and developed by OpenAI in San Francisco, it was the latest and strongest of its kind — a “large language model” capable of producing fluent text after having ingested billions of words from books, articles, and websites. According to the paper “Language Models are Few-Shot Learners” by OpenAI, GPT-3 was so advanced that many individuals had difficulty distinguishing between news stories generated by the model and those written

Datasets 64

Datasets Architecture Deep Learning SQL 64

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Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

Database

KDnuggets

JANUARY 18, 2023

7 Best Platforms to Practice SQL • Explainable AI: 10 Python Libraries for Demystifying Your Model's Decisions • ChatGPT: Everything You Need to Know • Data Lakes and SQL: A Match Made in Data Heaven • Google Data Analytics Certification Review for 2023

SQL 85

SQL Python Data Lake Certification 85

DataKitchen

JANUARY 18, 2023

While you’re admiring the latest cloud tech, don’t forget that humans have been debugging pipelines, at least since the Romans built the aqueducts. Any good plumber can give you some hard-won tips on managing data pipelines effectively, insights that might save your career from going down the drain. Your overalls are cleaner when you work on new construction. .

Data Pipeline 52

Data Pipeline Data AWS Data Engineering 52

Acceldata

JANUARY 18, 2023

Data insights, delivered through data observability, are critical for physical and digital retail success.

Retail 52

Retail Data 52

Snowflake

JANUARY 18, 2023

Genomic data, which is the DNA data of organisms, is essential to life sciences companies. For population studies, anonymized data sets can link long-term health histories with treatment patterns and genomic variations, making it possible to analyze effective approaches for subpopulations. In clinical trials and drug discovery, pharmaceutical research that combines patient health data, drug effectiveness, and genomic variations can improve outcomes and speed time to market.

Pharmaceutical 85

Pharmaceutical AWS Java Healthcare 85

Acceldata

JANUARY 18, 2023

Here is the definition of a data product, brought to you by the output of an actual data product.

Data 52

Data 52

Tweag

JANUARY 18, 2023

Tweagers have an engineering mantra — Functional. Typed. Immutable. — that begets composable software which can be reasoned about and avails itself to static analysis. These are all “good things” for building robust software, which inevitably lead us to using languages such as Haskell, OCaml and Rust. However, it would be remiss of us to snub languages that don’t enforce the same disciplines, but are nonetheless popular choices in industry.

Python 84

Python Bytes Food Software Engineer 84

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Certification

Acceldata

JANUARY 18, 2023

Poor data quality can lead to increased operational costs, security and compliance risks, and limit growth. Get a plan for increasing data quality.

Programming 40

Programming Data 40

Snowflake

JANUARY 18, 2023

SaaS providers enable business teams to work more efficiently and gain insights more quickly, driving value for their businesses. SaaS solutions can bring significant value to their organizations and adoption is widespread—companies typically use an average of 130 SaaS applications, according to a recent survey. While the benefits are great, SaaS apps can also create data silos and data copies across the organization.

Data Warehouse 52

Data Warehouse Cloud Accessible Accessibility 52

DoorDash Engineering

JANUARY 18, 2023

One of the great features of developing in SwiftUI is Xcode Previews which enable rapid UI iteration by rendering code changes in near real-time alongside the SwiftUI code. At DoorDash we make heavy use of Xcode Previews along with the SnapshotTesting library from Point-Free to ensure that screens look how we expect while developing them and ensure they don’t change in unexpected ways over time.

Coding 58

Coding Technology Engineering Project 58

Monte Carlo

JANUARY 18, 2023

Leveraging new data sources is a big part of scaling data adoption. But becoming a data-first organization is about more than just ingesting new data. The real challenge is what you do with all that data once you have it. And once you have it, how do you trust it? Here’s how Blend, a cloud infrastructure platform powering digital experiences for some of the world’s largest financial institutions, combined cloud-based data transforms and data observability to deliver trustworthy insights faster.

Cloud 52

Cloud Metadata SQL Banking 52

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Data Science