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All Blog Posts Tagged 'learning' (305)

Difference Between Algorithm and Artificial Intelligence

By 2035 AI could boost average profitability rates by 38 percent and lead to an economic increase of $14 Trillion.

  • Accenture

The words Artificial Intelligence (AI), and algorithms are most often misused and misunderstood. There are often used…

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Added by Aileen Scott on July 6, 2021 at 9:30pm — No Comments

Applying Regression-based Machine Learning to Web Scraping

Whenever we begin dealing with machine learning, we often turn to the simpler classification models. In fact, people outside of this sphere have mostly seen those models at work. After all, image recognition has become the poster child of machine learning.…

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Added by Aleksandras Sulzenko on June 17, 2021 at 9:30pm — No Comments

Best Programming Languages For AI & ML (Artificial Intelligence and Machine Learning)

Industries are walking the path that leads to digital transformation and automation, and artificial intelligence is the constant companion. Not many know that artificial intelligence remained stagnant for decades but is now undergoing massive growth and…

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Added by Lucky Brain on June 11, 2021 at 4:19am — No Comments

Approximation or Classification – which one to choose?

Among the many decisions you’ll have to make when building a predictive model is whether your business problem is either a classification or an approximation task. It’s an important decision because it determines which group of methods you choose to create a model: classification (decision trees, Naive Bayes) or approximation (regression tree,…

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Added by Algolytics on June 2, 2021 at 1:00am — No Comments

Potential Risk AI can cause to the world!

Source: Google

Artificial intelligence is among the most talked-about trends in recent years, and It is a 2 side blade with positives and negatives. Talking about positives, technologies are starting to improve our lives in multiple ways, from enhancing the healthcare…

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Added by Ved Raj on May 11, 2021 at 8:30pm — No Comments

The Key to Business Survival in the Era of AI

Build a Continuously Adaptive Learning Organization (CALO)



Among the most perplexing challenges facing CEOs in…

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Added by Mark Montgomery on May 4, 2021 at 2:30pm — No Comments

Your Guide for the Commonly Used Machine Learning Algorithms

We are currently living in such a period where computing has transformed immensely from large mainframes to personal computers to the cloud.  The constant technological progress and the evolution in computing resulted in major automation.

In this article, let’s understand few commonly used…

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Added by Aileen Scott on May 3, 2021 at 8:00pm — No Comments

How to Introduce Machine Learning to your Business

Artificial intelligence systems usually learn by example and are likely to learn better with high-quality examples. Low quality or insufficient training data can lead to unreliable systems that make poor decisions, reach the wrong conclusions, introduce or perpetuate bias and cannot handle real-world variation among other issues. Besides, poor data is…

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Added by Logan berger on March 21, 2021 at 5:00pm — No Comments

Can Deep Learning Address Limited Bandwidth and Other Video Streaming Challenges?

We all experience video streaming issues, probably on a daily basis. But now that people aren’t just streaming for entertainment, but are relying on it in many cases to perform their jobs, it ups the ante to address some of these issues and provide an improved experience. Deep…

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Added by John Burke on March 19, 2021 at 2:00pm — 1 Comment

Operationalizing AI – Introduction to the ModelOps Pipeline

Artificial Intelligence (AI) is all the buzz with everyone looking for ways to leverage AI in some capacity within their organization. Whether you’re running a business focused on insurance, construction, or anything in between, the list of companies adding AI or Data Science teams to help their business succeed is growing every day. Unfortunately for…

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Added by Clayton Davis on March 3, 2021 at 5:30am — No Comments

The Future of AI in Insurance

Artificial intelligence (AI) and machine learning have come a long way, both in terms of adoption across the broader technology landscape and the insurance industry specifically. That said, there is still much more territory to cover, helping…

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Added by Karin Golde on February 22, 2021 at 1:00pm — No Comments

How Machine Learning Discretely Assists Data Scientists

There are unlimited discussions, and conversations over this well-known point, and it tends to be a touch of overpowering to realize where to begin from data science specialists to finish amateurs.

While, from analysts to students,…

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Added by akash on February 4, 2021 at 11:30pm — No Comments

How big is the smart learning industry and how it will look like in the next 5 years?

According to global smart learning Industry analysis by Research Dive, the global industry forecast will be $74,179.1 million in 2026, at a 19.2% CAGR and is growing from $18,200.0 million in2018.

Smart Learning industry Drivers: Growing acceptance of e-learning in academic & corporate sectors…

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Added by Kedar Supekar on January 29, 2021 at 4:00am — No Comments

Blockchain emerging as Next-Generation Data and Model Governance Framework

Introduction and Motivation

The blockchain technology has led to a strong foundation for different applications related to asset management, medical/health, finance, and insurance. Data analytics provided by…
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Added by Sharmistha Chatterjee on December 28, 2020 at 1:30am — No Comments

Essential Machine Learning Algorithms That Data Analysts Need To Know

AI is taking over. In 2021, we’re going to see machine learning taking on a bigger role in data analysis as algorithms become capable of reducing error and producing more accurate models within themselves. These algorithms cover iterative processes, decision trees as well as multi-dimensional splitting of datasets. Machine learning is enabling data analysts to have new and greater insights, affecting everything from marketing departments to the way we learn. Here are the essential machine…

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Added by George J. Newton on December 23, 2020 at 12:00pm — No Comments

Is AI Getting Boring? And Some Thoughts on the Future of AI.

Summary:  Things are getting repetitious and that can be boring.  Still, looking at lessons from the 90s it’s clear there are at least one or two decades of important economic advances that will based on our current AI/ML.  Then some thoughts on where that next really huge breakthrough will come from that will return our initial excitement.

 …

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Added by William Vorhies on December 8, 2020 at 11:12am — No Comments

Using an AI COE (Center of Excellence) to Bridge from Experimentation to Mastery

Summary:  There is now sufficient experience among mid and large sized companies starting their AI journey to identify a single best practice for moving from AI experimentation to scale-up: the AI COE (Center of Excellence).

 

 

If you are a mid-sized business, government organization, or educational…

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Added by William Vorhies on December 2, 2020 at 3:18pm — No Comments

When Should a Machine Learning Model Be Retrained?

A few years ago, it was extremely uncommon to retrain a machine learning model with new observations systematically. This was mostly because the model retraining tasks were laborious and cumbersome, but machine learning has come a long way in a short time. Things have changed with the adoption of more sophisticated MLOps solutions.

Now, the…

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Added by Henrik Skogström on November 30, 2020 at 11:11pm — No Comments

Intelligent Automation – Just Add AI to your RPA

Summary:  Let’s start by clarifying the difference between RPA (Robotic Process Automation) and IA (Intelligent Automation).  Then we’ll show why AI/ML inside Intelligent Automation is the secret sauce that really makes this work.

 

As we’ve tracked the adoption of AI/ML across industries…

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Added by William Vorhies on November 18, 2020 at 9:00am — No Comments

When Is a Machine Learning Model Good Enough for Production, and How to Stress About It Only Once?

As you start incorporating machine learning models into your end-user applications, the question comes up: “When is the model good enough to deploy?”

There simply is no single right answer.

There is no clear-cut measure of when a machine learning model is ready to…

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Added by Henrik Skogström on November 18, 2020 at 5:30am — No Comments

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