Continuous Delivery for Machine Learning

Martin Fowler

Foiling fraud with machine learning

CTOvision

Read Caroline Hermon explain how machine learning can be used to foil cyber frauds on Tech Radar: Digital transformation has for years seemed like nothing but a buzzword.

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Machine Learning

DevOps.com

The post Machine Learning appeared first on DevOps.com. Blogs ROELBOB

All about Machine Learning

Hacker Earth Developers Blog

In our third episode of Breaking 404 , we caught up with Srivatsan Ramanujam, Director of Software Engineering: Machine Learning, Salesforce to discuss everything about Machine Learning and the best practices for ML engineers to excel in their careers.

Machine Learning for Builders: Tools, Trends, and Truths

Speaker: Rob De Feo, Startup Advocate at Amazon Web Services

Machine learning techniques are being applied to every industry, leveraging an increasing amount of data and ever faster compute. But that doesn’t mean machine learning techniques are a perfect fit for every situation (yet). So how can a startup harness machine learning for its own set of unique problems and solutions, and does it require a warehouse filled with PhDs to pull it off?

The Role of Machine Learning in DevOps

Kovair - DevOps

Artificial intelligence (AI) and machine learning (ML) are advanced technologies in the IT world. DevOps Technologies DevOps Consultants DevOps Implementation Machine Learning Why DevOps gained popularity

20 Machine Learning/Artificial Intelligence Influencers To Follow In 2020

Hacker Earth Developers Blog

Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% Consequently, there has been a significant increase in the number of Machine Learning enthusiasts across the globe.

20 Machine Learning/Artificial Intelligence Influencers To Follow In 2020

Hacker Earth Developers Blog

Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% Consequently, there has been a significant increase in the number of Machine Learning enthusiasts across the globe.

Five Challenges of Machine Learning DevOps

DevOps.com

As organizations add machine learning (ML) to their workflows, it’s tempting to try to squeeze model creation and deployment into the existing software development lifecycle (SDLC). The post Five Challenges of Machine Learning DevOps appeared first on DevOps.com.

A Buyer’s Guide to AI and Machine Learning

DevOps.com

The post A Buyer’s Guide to AI and Machine Learning appeared first on DevOps.com. AI Blogs ai artificial intelligence machine learning ml test oracleB2B software sales and marketing teams love hearing the term “artificial intelligence” (AI).

Difference between Artificial Intelligence and Machine Learning

The Crazy Programmer

We are talking about machine learning and artificial intelligence. Artificial Intelligence does not the system to be pre programmed however they are given algorithms which are able to learn on their own intelligence. . Generally having low intelligence (learning ability). Reactive Machine . Machine which are just able to react to some actions. Machine learning algorithms generally uses previous data and try to generate knowledge based on that data.

Prerequisites For Machine Learning

The Crazy Programmer

Machine Learning has rightly become one of the most popular technologies around and according to Artificial Intelligence (AI) researchers, every single thing ranging from our food, to our jobs, to the software we write will be affected by it. Prerequisites For Machine Learning.

IBM donates machine learning tooling to enable ‘responsible’ AI

CTOvision

is donating three open-source artificial intelligence development toolkits to LF AI, an organization within the Linux Foundation that maintains open-source machine learning tools. IBM Corp. The LF AI Technical Advisory Committee […].

Putting Machine Learning Models into Production

Cloudera Engineering

The key focus areas (detailed in the diagram below) are usually managed by machine learning engineers after the data scientists have done their work. To make this more concrete, I will use an example of telco customer churn (the “Hello World” of enterprise machine learning).

Machine learning for personalization

O'Reilly Media - Ideas

Continue reading Machine learning for personalization Tony Jebara explains how Netflix is personalizing and optimizing the images shown to subscribers.

Operationalizing machine learning

O'Reilly Media - Data

Dinesh Nirmal explains how real-world machine learning reveals assumptions embedded in business processes that cause expensive misunderstandings. Continue reading Operationalizing machine learning

Testing machine learning interpretability techniques

O'Reilly Media - Data

Interpreting machine learning models is a pretty hot topic in data science circles right now. Like others in the applied machine learning field, my colleagues and I at H2O.ai have been developing machine learning interpretability software for the past 18 months or so.

Machine Learning and the Production Gap

O'Reilly Media - Ideas

The biggest problem facing machine learning today isn’t the need for better algorithms; it isn’t the need for more computing power to train models; it isn’t even the need for more skilled practitioners. I first learned about Emmanuel through articles on his blog. )

Machine Learning: a whirlwind intro

A Cloud Guru

I’m Kesha Williams , an AWS Machine Learning Hero and Alexa Champion, and this is Kesha's Korner, where we learn about artificial intelligence and machine learning on AWS. Learn with me as we transform your engineering skills and future-proof your career!

How DevOps Powered by AI and Machine Learning Is Delivering Business Transformation

DevOps.com

The use of artificial intelligence (AI) and machine learning (ML) is fundamentally changing the way we think about DevOps. The post How DevOps Powered by AI and Machine Learning Is Delivering Business Transformation appeared first on DevOps.com.

Artificial intelligence (AI) vs. machine learning (ML): 8 common misunderstandings

CTOvision

Read Stephanie Overby bust some myths about machine learning and artificial intelligence on Enterprisers Project : Some people use the terms of artificial intelligence (AI) and machine learning (ML) interchangeably. […].

Machine learning: Research & industry

O'Reilly Media - Data

Having worked in both research and industry, Mikio Braun shares insights into what's the same, what's different, and how deep learning might change the game. Continue reading Machine learning: Research & industry

Freshly (un)retired, Gary McGraw takes on machine-learning security (Q&A)

The Parallax

The mirror, built by the CareOS subsidiary of the French tech company Baracoda , offers personalized recommendations guided by Google’s TensorFlow Lite machine-learning algorithm platform. READ MORE ON MACHINE LEARNING. Q: Why is securing machine learning important?

Building a Lakehouse with Databricks and Machine Learning

The New Stack

When it comes to data for machine learning (ML) applications, often times a database system just doesn’t cut it. To find out more about Databricks’ strategy in the age of AI, I spoke with Clemens Mewald , the company’s director of product management, data science and machine learning.

From Machine Learning to Machine Reasoning

CTOvision

The conversation around Artificial Intelligence usually revolves around technology-focused topics: machine learning, conversational interfaces, autonomous agents, and other aspects of data science, math, and implementation. Artificial Intelligence CTO News Cognilytica common sense deep learning knowledge graph machine learning machine reasoning ontology

R vs Python for Machine Learning

The Crazy Programmer

There are so many things to learn before to choose which language is good for Machine Learning. Don’t worry guys through this article we will discuss R vs Python for Machine Learning. R vs Python for Machine Learning. Deep Learning.

Simplifying machine learning lifecycle management

O'Reilly Media - Data

In this episode of the Data Show , I spoke with Harish Doddi , co-founder and CEO of Datatron , a startup focused on helping companies deploy and manage machine learning models. Continue reading Simplifying machine learning lifecycle management

5 Steps to Making Better Business Decisions with Machine Learning

Cloudera Engineering

My colleague Matthiew Lamarisse has built a really great end-to-end project that we use to demo data science and machine learning workflows in CDSW/CML. That means we have to make the decision to use data science and machine learning to get our wine a better rating.

Developing Simple and Stable Machine Learning Models

DevOps.com

A current challenge and debate in artificial intelligence is building simple and stable machine learning models capable of identifying patterns and even objects. The post Developing Simple and Stable Machine Learning Models appeared first on DevOps.com.

How OpenXcell is adapting to TensorFlow to building advanced machine learning models

Openxcell

Tensorflow for Machine Learning helps engineers effectively to assemble and send ML-fueled applications. With the help of TensorFlow.js, you can create new machine learning models, and it can be deployed to the existing models through JavaScript.

When machine learning matters

Erik Bernhardsson

I joined Spotify in 2008 to focus on machine learning and music recommendations. In the majority of all products, machine learning will not be a key differentiator in the first five years. Most machine learning is sprinkles on the top. I lead the tech team at a startup and we are nowhere near using any kind of sophisticated machine learning, two years into the process. Rarely is machine learning the fundamental enabler of a product.

Aspects of Machine Learning on the Edge

DevOps.com

Machine learning (ML) is hard. The post Aspects of Machine Learning on the Edge appeared first on DevOps.com. Blogs DevOps Practice DevOps Toolbox Doin' DevOps devops machine learning ml

Managing risk in machine learning models

O'Reilly Media - Data

Burt recently co-authored a white paper on managing risk in machine learning models , and I wanted to sit down with them to discuss some of the proposals they put forward to organizations that are deploying machine learning.

Preparing Your Dataset for Machine Learning

A Cloud Guru

Hi, I’m Kesha Williams , an AWS Machine Learning Hero and Alexa Champion. This is Kesha's Korner, where we learn about artificial intelligence and machine learning on AWS. Come learn with me as we transform your engineering skills and future-proof your career!

Machine Learning

I'm Programmer

The post Machine Learning appeared first on I'm Programmer. Programming Funny Images Programming Jokes Machine Learning machine learning applications role of Computer Science in Machine Learning

How will the GDPR impact machine learning?

O'Reilly Media - Data

Answers to the three most commonly asked questions about maintaining GDPR-compliant machine learning programs. But there’s perhaps no more important—or uncertain—question than how the regulation will impact machine learning (ML), in particular.

Machine Learning: Cutting Through the Hype

The New Stack

Every technology vendor, it seems, is taking advantage of the buzz around machine learning (ML), especially in cybersecurity, where vendors know that their clients need to keep pace with ever more intelligent threats. Machine learning is a perfect example.