TechCrunch

JULY 12, 2022

Machine learning can provide companies with a competitive advantage by using the data they’re collecting — for example, purchasing patterns — to generate predictions that power revenue-generating products (e.g. At a high level, Tecton automates the process of building features using real-time data sources.

Artificial Inteligence 249

Artificial Inteligence Machine Learning Marketing Data Engineering 249

CIO

SEPTEMBER 29, 2023

Most relevant roles for making use of NLP include data scientist , machine learning engineer, software engineer, data analyst , and software developer. They’re also seeking skills around APIs, deep learning, machine learning, natural language processing, dialog management, and text preprocessing.

Generative AI 357

Generative AI ChatGPT Machine Learning Artificial Inteligence 357

TechCrunch

APRIL 12, 2022

Union.ai , a startup emerging from stealth with a commercial version of the open source AI orchestration platform Flyte, today announced that it raised $10 million in a round contributed by NEA and “select” angel investors. “Data science is very academic, which directly affects machine learning.

Artificial Inteligence 202

Artificial Inteligence Machine Learning Open Source Biotech 202

TechCrunch

APRIL 11, 2023

When DBeaver creator Serge Rider began building an open source database admin tool in 2013, he probably had no idea that 10 years later, it would boast more than 8 million users. So actually anyone who needs to work with data can use DBeaver,” she told TechCrunch.

Open Source 203

Open Source Database Administration Machine Learning Artificial Inteligence 203

d2iq

FEBRUARY 19, 2021

Going from a prototype to production is perilous when it comes to machine learning: most initiatives fail , and for the few models that are ever deployed, it takes many months to do so. As little as 5% of the code of production machine learning systems is the model itself. Adapted from Sculley et al.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

DataRobot

MARCH 10, 2022

This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). This type of growth has stressed legacy data management systems and makes it nearly impossible to implement a profitable data-centered solution. Factory Monitoring?—?

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning IoT 52

Cloudera

JULY 24, 2023

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

Open Source 66

Open Source Analytics Software Review Metrics 66

CIO

JUNE 14, 2023

Candidates are required to complete a minimum of 12 credits, including four required courses: Algorithms for Data Science, Probability and Statistics for Data Science, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization.

Big Data 317

Big Data Analytics Data eLearning 317

CIO

JULY 10, 2023

For a decade, Edmunds, an online resource for automotive inventory and information, has been struggling to consolidate its data infrastructure. Now, with the infrastructure side of its data house in order, the California-based company is envisioning a bold new future with AI and machine learning (ML) at its core.

Infrastructure 246

Infrastructure Artificial Inteligence Data Generative AI 246

Confluent

FEBRUARY 6, 2019

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. Impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 106

Machine Learning Artificial Inteligence Scalability Data Engineering 106

O'Reilly Media - Ideas

NOVEMBER 13, 2018

As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations. We recently conducted a survey which garnered more than 11,000 respondents—our main goal was to ascertain how enterprises were using machine learning. Privacy and security.

Machine Learning 92

Machine Learning Artificial Inteligence Software Review Conference 92

TechCrunch

MAY 10, 2022

“The major challenges we see today in the industry are that machine learning projects tend to have elongated time-to-value and very low access across an organization. “Given these challenges, organizations today need to choose between two flawed approaches when it comes to developing machine learning. .

Artificial Inteligence 235

Artificial Inteligence Machine Learning Off-The-Shelf Training 235

O'Reilly Media - Data

JULY 18, 2018

In this short talk, I describe some interesting trends in how data is valued, collected, and shared. Economic value of data. It’s no secret that companies place a lot of value on data and the data pipelines that produce key features. But if data is precious, how do we go about estimating its value?

Machine Learning 134

Machine Learning Artificial Inteligence Data Marketing 134

CIO

JUNE 7, 2022

Predictive analytics applies techniques such as statistical modeling, forecasting, and machine learning to the output of descriptive and diagnostic analytics to make predictions about future outcomes. In business, predictive analytics uses machine learning, business rules, and algorithms. Data analytics tools.

Analytics 338

Analytics Data Analysis Business Analytics 338

Altexsoft

MAY 27, 2020

Machine learning (ML) history can be traced back to the 1950s, when the first neural networks and ML algorithms appeared. Analysis of more than 16.000 papers on data science by MIT technologies shows the exponential growth of machine learning during the last 20 years pumped by big data and deep learning advancements.

Machine Learning 89

Machine Learning Artificial Inteligence Architecture Training 89

CIO

SEPTEMBER 2, 2022

In the finance industry, software engineers are often tasked with assisting in the technical front-end strategy, writing code, contributing to open-source projects, and helping the company deliver customer-facing services. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

AUGUST 31, 2022

In the finance industry, software engineers are often tasked with assisting in the technical front-end strategy, writing code, contributing to open-source projects, and helping the company deliver customer-facing services. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

TechCrunch

FEBRUARY 2, 2022

RudderStack , a platform that focuses on helping businesses build their customer data platforms to improve their analytics and marketing efforts, today announced that it has raised a $56 million Series B round led by Insight Partners, with previous investors Kleiner Perkins and S28 Capital also participating.

Data 204

Data Machine Learning Artificial Inteligence Architecture 204

Cloudera

JANUARY 20, 2021

Machine learning is now being used to solve many real-time problems. One big use case is with sensor data. Corporations now use this type of data to notify consumers and employees in real-time. With this example as inspiration, I decided to build off of sensor data and serve results from a model in real-time.

Machine Learning 113

Machine Learning Artificial Inteligence Applications Data 113

Exadel

FEBRUARY 20, 2023

The technological landscape has evolved to include AI assistants, self-driving cars, and machine learning solutions that process data in a blink of an eye. Major Players for AI in the Cloud For the scope of this article, AI is defined as machine learning, since ML is the biggest constituent of the technology.

Artificial Inteligence 52

Artificial Inteligence Cloud Machine Learning Azure 52

TechCrunch

NOVEMBER 28, 2022

Artificial intelligence promises to help, and maybe even replace, humans to carry out everyday tasks and solve problems that humans have been unable to tackle, yet ironically, building that AI faces a major scaling problem. “This is where V7’s AI Data Engine shines.

Training 240

Training Data Technical Review Artificial Inteligence 240

TechCrunch

MARCH 23, 2022

At that time, the scrappy data analytics company had scooped up $3.5 million in funding to develop its tool for what happens after you’ve collected a bunch of data, namely assembling and organizing it so the data can be analyzed. Data collection isn’t the problem: It’s what companies are doing with it.

Open Source 213

Open Source Data Engineering Strategic Planning Analytics 213

O'Reilly Media - Ideas

AUGUST 18, 2020

That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows. This is an open question, but we’re putting our money on best-of-breed products. A little of both?

Machine Learning 144

Machine Learning Artificial Inteligence Data Data Engineering 144

TechCrunch

JANUARY 10, 2023

Observability tools to capture and analyze IT tool data aren’t new — and these days, they’re raising a respectable amount of capital. Monte Carlo , whose platform uses machine learning to infer what data looks like and assess its impact, became a unicorn last May with $135 million in funding.

Data 241

Data Software Review Technical Review Systems Review 241

O'Reilly Media - Ideas

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. that support unsupervised learning.

Artificial Inteligence 115

Artificial Inteligence Trends Artificial Intelligence Machine Learning 115

Netflix Tech

MARCH 7, 2024

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

System 90

System Machine Learning Artificial Inteligence Training 90

Capgemini

JANUARY 17, 2023

By creating a lakehouse, a company gives every employee the ability to access and employ data and artificial intelligence to make better business decisions. Many organizations that implement a lakehouse as their key data strategy are seeing lightning-speed data insights with horizontally scalable data-engineering pipelines.

Strategy 52

Strategy Technical Review Data Artificial Inteligence 52

Cloudera

JUNE 26, 2023

Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models.

Tools 76

Tools Data Engineering Analytics Testing 76

The Citus Data

MARCH 31, 2023

Americas livestream, Citus open source user, real-time analytics, JSONB) Lessons learned: Migrating from AWS-Hosted PostgreSQL RDS to Self-Hosted Citus , by Matt Klein & Delaney Mackenzie of Jellyfish.co. (on-demand Lots to learn from here! And the speakers cover a broad range of interesting topics.

Azure 85

Azure Open Source Virtualization Software Engineering 85

Cloudera

OCTOBER 5, 2020

Cloudera Data Platform Powered by NVIDIA RAPIDS Software Aims to Dramatically Increase Performance of the Data Lifecycle Across Public and Private Clouds. This exciting initiative is built on our shared vision to make data-driven decision-making a reality for every business. Compared to previous CPU-based architectures, CDP 7.1

Enterprise 91

Enterprise Cloud Data Machine Learning 91

O'Reilly Media - Ideas

JANUARY 8, 2019

In a recent O’Reilly survey , we found that the skills gap remains one of the key challenges holding back the adoption of machine learning. The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. Continuing investments in (emerging) data technologies. Burgeoning IoT technologies.

Trends 89

Trends Data Machine Learning Artificial Inteligence 89

CTOvision

JUNE 15, 2015

You know Spark, the free and open source complement to Apache Hadoop that gives enterprises better ability to field fast, unified applications that combine multiple workloads, including streaming over all your data. They also launched a plan to train over a million data scientists and data engineers on Spark.

Open Source 117

Open Source Big Data Machine Learning Artificial Inteligence 117

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. Apache Iceberg’s real superpower is its community.

Data 92

Data Analytics Open Source Architecture 92

Cloudera

FEBRUARY 25, 2021

Cloudera has a front-row seat to organizational challenges as those enterprises make Machine Learning a core part of their strategies and businesses. The work of a machine learning model developer is highly complex. We work with the largest companies in the world to help tackle their most challenging ML problems.

Machine Learning 83

Machine Learning Artificial Inteligence Telecommunications Enterprise 83

O'Reilly Media - Ideas

DECEMBER 6, 2018

In this post, I share slides and notes from a keynote Roger Chen and I gave at the Artificial Intelligence conference in London in October 2018. To assess the state of adoption of machine learning (ML) and AI, we recently conducted a survey that garnered more than 11,000 respondents. is extremely high.

Technology 79

Technology Artificial Inteligence Machine Learning Hardware 79

Hu's Place - HitachiVantara

MAY 10, 2019

Rule-based fraud detection software is being replaced or augmented by machine-learning algorithms that do a better job of recognizing fraud patterns that can be correlated across several data sources. Fraud detection software developed in the past have traditionally been based on rules -based models.

Data 90

Data Machine Learning Artificial Inteligence Weak Development Team 90

Altexsoft

AUGUST 25, 2021

What is Natural Language Processing? Natural language processing or NLP is a branch of Artificial Intelligence that gives machines the ability to understand natural human speech. NLP techniques open tons of opportunities for human-machine interactions that we’ve been exploring for decades.

Tools 139

Tools Artificial Inteligence Technical Review Systems Review 139