Analytics Vidhya

JULY 25, 2022

Introduction The gradient descent algorithm is an optimization algorithm mostly used in machine learning and deep learning. In linear regression, it finds weight and biases, and deep learning backward propagation uses the […]. This article was published as a part of the Data Science Blogathon.

Deep Learning 364

Deep Learning IT Machine Learning Data Science 364

Analytics Vidhya

NOVEMBER 20, 2024

In machine learning, a similar challenge exists with gradient descent, where using […] The post What is Adaptive Gradient(Adagrad) Optimizer? If you used the same amount of water on all of them every day, some plants would thrive, while others might get overwatered or dry out. appeared first on Analytics Vidhya.

Optimization 288

Optimization Machine Learning Analytics Deep Learning 288

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, model validation, results visualization and model optimization.

Data Science 341

Data Science Data Lake Data mining Deep Learning 341

Rocket-Powered Data Science

DECEMBER 16, 2018

So, you start by assuming a value for k and making random assumptions about the cluster means, and then iterate until you find the optimal set of clusters, based upon some evaluation metric. The above example (clustering) is taken from unsupervised machine learning (where there are no labels on the training data).

Machine Learning 203

Machine Learning Metrics Optimization Data Science 203

Analytics Vidhya

JANUARY 29, 2024

But, here’s the problem: this encyclopedia is huge and requires significant time and effort […] The post Optimizing Neural Networks: Unveiling the Power of Quantization Techniques appeared first on Analytics Vidhya. Now, this friend has a precise way of doing things, like he has a dictionary in his head.

Optimization 315

Optimization Analytics IoT Deep Learning 315

CIO Business Intelligence

NOVEMBER 27, 2024

Recent research shows that 67% of enterprises are using generative AI to create new content and data based on learned patterns; 50% are using predictive AI, which employs machine learning (ML) algorithms to forecast future events; and 45% are using deep learning, a subset of ML that powers both generative and predictive models.

Data Architecture 128

Data Architecture Cost-Benefit Machine Learning Experimentation 128

KDnuggets

DECEMBER 1, 2023

Curious about optimizing AI for everyday devices? Dive into the complete overview of MIT's TinyML and Efficient Deep Learning Computing course. Explore strategies to make AI smarter on small devices. Read the full article for an in-depth look!

Deep Learning 153

Deep Learning Optimization Strategy Machine Learning 153

O'Reilly on Data

DECEMBER 10, 2019

Roughly a year ago, we wrote “ What machine learning means for software development.” Karpathy suggests something radically different: with machine learning, we can stop thinking of programming as writing a step of instructions in a programming language like C or Java or Python. Instead, we can program by example.

Software 329

Software Machine Learning Risk Data-driven 329

Domino Data Lab

MARCH 11, 2021

Machine learning (ML) frameworks are interfaces that allow data scientists and developers to build and deploy machine learning models faster and easier. Machine learning is used in almost every industry, notably finance , insurance , healthcare , and marketing. Parameter Optimization.

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

Smart Data Collective

NOVEMBER 1, 2020

Machines, artificial intelligence (AI), and unsupervised learning are reshaping the way businesses vie for a place under the sun. With that being said, let’s have a closer look at how unsupervised machine learning is omnipresent in all industries. What Is Unsupervised Machine Learning? The Bottom Line.

Machine Learning 145

Machine Learning Data mining Visualization Statistics 145

IBM Big Data Hub

MAY 10, 2024

Underpinning most artificial intelligence (AI) deep learning is a subset of machine learning that uses multi-layered neural networks to simulate the complex decision-making power of the human brain. Deep learning requires a tremendous amount of computing power.

Deep Learning 101

Deep Learning Cost-Benefit Manufacturing Optimization 101

CIO Business Intelligence

JUNE 2, 2022

Recent notable research from the University of Cambridge, enabled by energy efficient HPC, includes a study on transformational machine learning (TML) and another on a robotic approach to reproducing research results. . Teaching Machines to ‘Learn How to Learn’. Just starting out with analytics?

Machine Learning 142

Machine Learning Deep Learning Data Quality Strategy 142

Smart Data Collective

NOVEMBER 9, 2022

There are a number of great applications of machine learning. One of the biggest benefits is testing processes for optimal effectiveness. The main purpose of machine learning is to partially or completely replace manual testing. Machine learning is used in many industries. Top ML Companies.

Machine Learning 122

Machine Learning Testing Cost-Benefit Data-driven 122

Domino Data Lab

JULY 10, 2019

New tools are constantly being added to the deep learning ecosystem. For example, there have been multiple promising tools created recently that have Python APIs, are built on top of TensorFlow or PyTorch , and encapsulate deep learning best practices to allow data scientists to speed up research.

Deep Learning 110

Deep Learning Visualization Recreation/Entertainment Data Processing 110

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

Management 363

Management Machine Learning Experimentation Metrics 363

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. . Collaboration and Sharing.

Testing 300

Testing Machine Learning Consulting Data Science 300

Analytics Vidhya

FEBRUARY 27, 2024

In this article, we will explore the features of Ayanza, its benefits, how to […] The post Optimize Project and Team Management With AI appeared first on Analytics Vidhya. With the advancement of technology, various tools have been developed to streamline these processes and enhance productivity.

Optimization 179

Optimization Management Technology Analytics 179

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. Introduction Machine learning models often behave unpredictably, as data scientists would be the first to tell you. A more general approach is to learn a Generalized Additive Model (GAM).

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Why aren’t traditional software tools sufficient?

Modeling 249

Modeling Machine Learning Testing Metrics 249

Cloudera

FEBRUARY 11, 2022

Advances in the development and application of Machine Learning (ML) and Deep Learning (DL) algorithms, require greater care to ensure that the ethics embedded in previous rule-based systems are not lost. What is Machine Learning. Instead, they are learned by training a model on data.

Machine Learning 97

Machine Learning Sales Data Science Deep Learning 97

O'Reilly on Data

MARCH 7, 2019

Language understanding benefits from every part of the fast-improving ABC of software: AI (freely available deep learning libraries like PyText and language models like BERT ), big data (Hadoop, Spark, and Spark NLP ), and cloud (GPU's on demand and NLP-as-a-service from all the major cloud providers). negation) detection.

Deep Learning 279

Deep Learning Testing Machine Learning Modeling 279

Domino Data Lab

AUGUST 22, 2019

Many thanks to Addison-Wesley Professional for providing the permissions to excerpt “Natural Language Processing” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. Introduction.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI In this post, we shed some light on various efforts toward generating data for machine learning (ML) models. Machine learning applications rely on three main components: models, data, and compute.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

Rocket-Powered Data Science

DECEMBER 15, 2018

This wisdom applies not only to life but to machine learning also. Specifically, the availability and application of labeled data (things past) for the labeling of previously unseen data (things future) is fundamental to supervised machine learning. A related problem also arises in unsupervised machine learning.

Machine Learning 171

Machine Learning Optimization Metrics Deep Learning 171

IBM Big Data Hub

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other? Machine learning is a subset of AI.

Deep Learning 56

Deep Learning Machine Learning Unstructured Data Modeling 56

O'Reilly on Data

OCTOBER 19, 2021

Much has been written about struggles of deploying machine learning projects to production. This approach has worked well for software development, so it is reasonable to assume that it could address struggles related to deploying machine learning in production too. However, the concept is quite abstract.

IT 364

IT Testing Experimentation Software 364

Occam's Razor

MARCH 30, 2017

Machine Learning | Marketing. Machine Learning | Analytics. People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Machine Learning | Marketing.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

CIO Business Intelligence

FEBRUARY 6, 2025

Think about it: LLMs like GPT-3 are incredibly complex deep learning models trained on massive datasets. In retail, they can personalize recommendations and optimize marketing campaigns. Even basic predictive modeling can be done with lightweight machine learning in Python or R. Theyre impressive, no doubt.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

DataRobot Blog

APRIL 22, 2022

In our previous post , we talked about how red AI means adding computational power to “buy” more accurate models in machine learning , and especially in deep learning. Since these blog posts were written, a lot has happened in the world and in machine learning.

Machine Learning 98

Machine Learning Measurement Deep Learning Manufacturing 98

O'Reilly on Data

JUNE 7, 2022

And granted, a lot can be done to optimize training (and DeepMind has done a lot of work on models that require less energy). That’s an allusion to the debate ( sometimes on Twitter ) between LeCun and Gary Marcus, who has argued many times that combining deep learning with symbolic reasoning is the only way for AI to progress. (In

Modeling 364

Modeling Interactive Optimization Deep Learning 364

DataRobot

JULY 27, 2021

Algorithmia automates machine learning deployment, provides maximum tooling flexibility, optimizes collaboration between operations and development, and leverages existing software development lifecycle (SDLC) and continuous integration/continuous development (CI/CD) practices. We couldn’t agree more.

Optimization 98

Optimization Modeling Machine Learning Deep Learning 98

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Cloudera

DECEMBER 4, 2024

Today, Artificial Intelligence (AI) and Machine Learning (ML) are more crucial than ever for organizations to turn data into a competitive advantage. Model servers are responsible for running models using highly optimized frameworks, which we will cover in detail in a later post. Why did we build it?

Metrics 73

Metrics Data Processing Machine Learning Deep Learning 73

IBM Big Data Hub

DECEMBER 20, 2023

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. What is machine learning?

Machine Learning 73

Machine Learning Modeling Deep Learning Predictive Modeling 73

IBM Big Data Hub

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

Machine Learning 64

Machine Learning Optimization Unstructured Data Sales 64

Jen Stirrup

MAY 5, 2020

You can also use Azure Data Lake storage as well, which is optimized for high-performance analytics. Apache Spark also allows you to do Machine Learning, streaming analytics, interactive querying, and also data visualization, as well. The Azure Data Lake Store is an optimized way of storing data, especially for analytics.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

Data Science 101

FEBRUARY 15, 2020

Announcements around an exciting new open-source deep learning library, a new data challenge and more. Microsoft Releases DeepSpeed for Training very large Models DeepSpeed is a new open-source library for deep learning optimization. An Intuitive Approach to Machine Learning Models.

Data Science 112

Data Science Deep Learning Machine Learning Modeling 112