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.

Machine Learning

DevOps.com

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

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

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

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

Applied machine learning at Facebook

O'Reilly Media - Ideas

Continue reading Applied machine learning at Facebook Kim Hazelwood discusses the hardware and software Facebook has designed to meet its scale needs.

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

Sustaining machine learning in the enterprise

O'Reilly Media - Data

Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning. Continue reading Sustaining machine learning in the enterprise

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

Sustaining machine learning in the enterprise

O'Reilly Media - Ideas

Drawing insights from recent surveys, Ben Lorica analyzes important trends in machine learning. Continue reading Sustaining machine learning in the enterprise

Cautionary allegory about machine learning

I'm Programmer

The post Cautionary allegory about machine learning appeared first on I'm Programmer. Programming Funny Images Programming Jokes Cautionary allegory about machine learning Machine Learning Algorithms Machine Learning For Beginners Understanding AI 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.

Why it’s hard to design fair machine learning models

O'Reilly Media - Data

They recently wrote a survey paper, “A Critical Review of Fair Machine Learning,” where they carefully examined the standard statistical tools used to check for fairness in machine learning models. Continue reading Why it’s hard to design fair machine learning models

Preserving privacy and security in machine learning

O'Reilly Media - Data

Ben Lorica offers an overview of recent tools for building privacy-preserving and secure machine learning products and services. Continue reading Preserving privacy and security in machine learning

MLflow: A platform for managing the machine learning lifecycle

O'Reilly Media - Data

Although machine learning (ML) can produce fantastic results, using it in practice is complex. Machine learning workflow challenges. MLflow: An open machine learning platform. We need to build machine learning tools to augment machine learning engineers”.

Using machine learning to improve dialog flow in conversational applications

O'Reilly Media - Data

Continue reading Using machine learning to improve dialog flow in conversational applications The O’Reilly Data Show Podcast: Alan Nichol on building a suite of open source tools for chatbot developers.

Machine Learning in iOS

VironIT

Fifty years ago, machine learning was still the stuff of science fiction. Machine learning is a type of artificial intelligence where computers “learn” without being explicitly programmed.

Becoming a machine learning company means investing in foundational technologies

O'Reilly Media - Ideas

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. A famous example is Google’s machine translation system, which shifted from “stats focused” approaches to TensorFlow.

What machine learning engineers need to know

O'Reilly Media - Data

This conversation grew out of a recent email thread the three of us had on machine learning engineers , a new job role that LinkedIn recently pegged as the fastest growing job in the U.S. Continue reading What machine learning engineers need to know

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.

Deep automation in machine learning

O'Reilly Media - Ideas

In a previous post , we talked about applications of machine learning (ML) to software development, which included a tour through sample tools in data science and for managing data infrastructure. But this process only applies to a single machine learning platform: Spark.

Privacy in the age of machine learning

O'Reilly Media - Data

Ben Lorica explores emerging security best practices for business intelligence, machine learning, and mobile computing products. Continue reading Privacy in the age of machine learning

Machine learning on encrypted data

O'Reilly Media - Ideas

The O’Reilly Data Show Podcast: Alon Kaufman on the interplay between machine learning, encryption, and security. As I noted, the main motivation for improving data liquidity is the growing importance of machine learning.

Managing risk in machine learning

O'Reilly Media - Ideas

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.

Machine Learning and Deep Learning: How Does Machine Learning Work?

G2 Crowd Software

anytime soon, but machine learning and deep learning are gaining a large amount of traction, and are becoming borderline essential in the business world. So what is machine learning and why is it so crucial for enterprise businesses today? Supervised learning.

Kong Applies Machine Learning to Microservice Management

The New Stack

Kong, the company building out a service control platform based on the open source Kong API gateway, has added artificial intelligence and machine learning — Kong Brain and Kong Immunity — to the mix to help provide visibility, security and governance at scale.

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.

Primer: Kubeflow Streamlines Machine Learning with Kubernetes

The New Stack

This article is a post in a series on bringing continuous integration and deployment (CI/CD) practices to machine learning. Kubeflow was created to make it easier to develop, deploy and manage machine learning applications. Kubernetes Machine Learning Technology

The State of the Octoverse: machine learning

Github

In our 2018 Octoverse report, we noticed machine learning and data science were popular topics on GitHub. We decided to dig a little deeper into the state of machine learning and data science on GitHub. Popular machine learning and data science packages.

How Kubernetes Could Orchestrate Machine Learning Pipelines

The New Stack

This article is a post in a series on bringing continuous integration and deployment (CI/CD) practices to machine learning. As a scalable orchestration platform, Kubernetes is proving a good match for machine learning deployment — in the cloud or on your own infrastructure.

Humans and the machine: Machine learning in context

O'Reilly Media - Data

Continue reading Humans and the machine: Machine learning in context Jean-François Puget explains why human context should be embraced as a guide to building better and smarter systems.

How AI and machine learning are improving customer experience

O'Reilly Media - Ideas

What can artificial intelligence (AI) and machine learning (ML) do to improve customer experience? One common application of machine learning and AI to customer experience is in personalization and recommendation systems. You created a machine learning application.

Machine learning and AI technologies and platforms at AWS

O'Reilly Media - Data

Dan Romuald Mbanga walks through the ecosystem around the machine learning platform and API services at AWS. Continue reading Machine learning and AI technologies and platforms at AWS

Applications of data science and machine learning in financial services

O'Reilly Media - Ideas

Chong has extensive experience using analytics and machine learning in financial services, and he has experience building data science teams in the U.S. Continue reading Applications of data science and machine learning in financial services