KDnuggets

OCTOBER 16, 2023

Check this list of free books for learning Python, statistics, linear algebra, machine learning and deep learning. Want to break into data science?

Data Science 151

Data Science Deep Learning Statistics Machine Learning 151

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

Machine Learning 57

Machine Learning Data Science Statistics Deep Learning 57

Rocket-Powered Data Science

JULY 6, 2023

These AI applications are essentially deep machine learning models that are trained on hundreds of gigabytes of text and that can provide detailed, grammatically correct, and “mostly accurate” text responses to user inputs (questions, requests, or queries, which are called prompts). Guess what? It isn’t.

Statistics 151

Statistics Deep Learning Machine Learning Modeling 151

Insight

MAY 14, 2020

In this post, I demonstrate how deep learning can be used to significantly improve upon earlier methods, with an emphasis on classifying short sequences as being human, viral, or bacterial. As I discovered, deep learning is a powerful tool for short sequence classification and is likely to be useful in many other applications as well.

Deep Learning 98

Deep Learning Statistics Modeling Software 98

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 69

Machine Learning Optimization Unstructured Data Sales 69

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 132

Machine Learning Data mining Visualization Statistics 132

KDnuggets

OCTOBER 27, 2023

This week on KDnuggets: Go from learning what large language models are to building and deploying LLM apps in 7 steps • Check this list of free books for learning Python, statistics, linear algebra, machine learning and deep learning • And much, much more!

Deep Learning 107

Deep Learning Data Science Statistics Machine Learning 107

KDnuggets

OCTOBER 10, 2022

It includes SQL, web scraping, statistics, data wrangling and visualization, business intelligence, machine learning, deep learning, NLP, and super cheat sheets. The only cheat you need for a job interview and data professional life.

Data Science 159

Data Science Deep Learning Statistics Machine Learning 159

O'Reilly on Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. If you’re using Python and deep learning libraries, the CleverHans and Foolbox packages can also help you debug models and find adversarial examples. 2] The Security of Machine Learning. [3]

Machine Learning 190

Machine Learning Modeling Testing Risk Management 190

Smart Data Collective

AUGUST 20, 2021

As we said in the past, big data and machine learning technology can be invaluable in the realm of software development. Machine learning technology has become a lot more important in the app development profession. Machine learning can be surprisingly useful when it comes to monetizing apps.

Machine Learning 88

Machine Learning Data mining Advertising Deep Learning 88

KDnuggets

DECEMBER 13, 2023

This week on KDnuggets: A collection of super cheat sheets that covers basic concepts of data science, probability & statistics, SQL, machine learning, and deep learning • An exploration of NotebookLM, its functionality, limitations, and advanced features essential for researchers and scientists • And much, much more!

Data Science 93

Data Science Deep Learning Statistics Machine Learning 93

Sanjeev Mohan

SEPTEMBER 14, 2020

Databases are enhancing capabilities to build, train and validate machine learning models right where the data sits – inside the databases and data warehouses. The post Databases and Machine Learning Coalesce appeared first on Sanjeev Mohan. The boundaries between data management and advanced analytics are blurring fast.

Machine Learning 93

Machine Learning Data Warehouse Deep Learning Statistics 93

Analytics Vidhya

JUNE 5, 2023

With their expertise in statistics, machine learning, AI, and programming, they are able to […] The post Data Scientist’s Insights: Strategies for Innovation and Leadership appeared first on Analytics Vidhya.

Strategy 209

Strategy Statistics Machine Learning Data-driven 209

Analytics Vidhya

MAY 22, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In Machine learning or Deep Learning, some of the models. The post How to transform features into Normal/Gaussian Distribution appeared first on Analytics Vidhya.

Deep Learning 280

Deep Learning Machine Learning Data Science Publishing 280

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

CIO Business Intelligence

JANUARY 26, 2024

Carnegie Mellon University The Machine Learning Department of the School of Computer Science at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning.

Machine Learning 99

Machine Learning Statistics Recreation/Entertainment Data Science 99

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. 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.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Smart Data Collective

JANUARY 13, 2022

It is obvious from the statistics that each customer, facing a bad customer service experience, does more than one step to hurt the business. Artificial intelligence and machine learning tools have advanced over the years. For example, deep learning can be used to understand speech and also respond with speech.

Machine Learning 123

Machine Learning Cost-Benefit Marketing Deep Learning 123

CIO Business Intelligence

JANUARY 24, 2024

It’s the culmination of a decade of work on deep learning AI. Deep learning AI: A rising workhorse Deep learning AI uses the same neural network architecture as generative AI, but can’t understand context, write poems or create drawings. You probably know that ChatGPT wasn’t built overnight.

Deep Learning 83

Deep Learning Unstructured Data Machine Learning Modeling 83

CIO Business Intelligence

OCTOBER 13, 2023

It’s a role that requires experience with natural language processing , coding languages, statistical models, and large language and generative AI models. This role is responsible for training, developing, deploying, scheduling, monitoring, and improving scalable machine learning solutions in the enterprise.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

CIO Business Intelligence

JANUARY 19, 2024

The US Bureau of Labor Statistics (BLS) forecasts employment of data scientists will grow 35% from 2022 to 2032, with about 17,000 openings projected on average each year. Companies are increasingly eager to hire data professionals who can make sense of the wide array of data the business collects.

Data Science 122

Data Science Machine Learning Predictive Modeling Experimentation 122

Domino Data Lab

AUGUST 9, 2021

Before selecting a tool, you should first know your end goal – machine learning or deep learning. Machine learning identifies patterns in data using algorithms that are primarily based on traditional methods of statistical learning. Machine Learning Modeling Tools.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

CIO Business Intelligence

APRIL 25, 2022

The data science path you ultimately choose will depend on your skillset and interests, but each career path will require some level of programming, data visualization, statistics, and machine learning knowledge and skills. It culminates with a capstone project that requires creating a machine learning model.

Data Science 145

Data Science Machine Learning Deep Learning Statistics 145

CIO Business Intelligence

MAY 20, 2022

The Machine Learning Department at Carnegie Mellon University was founded in 2006 and grew out of the Center for Automated Learning and Discovery (CALD), itself created in 1997 as an interdisciplinary group of researchers with interests in statistics and machine learning. Carnegie Mellon University.

Machine Learning 144

Machine Learning Statistics Recreation/Entertainment Data Science 144

Smart Data Collective

JUNE 4, 2021

Data science needs knowledge from a variety of fields including statistics, mathematics, programming, and transforming data. Mathematics, statistics, and programming are pillars of data science. In data science, use linear algebra for understanding the statistical graphs. It is the building block of statistics.

Data Science 104

Data Science Statistics Deep Learning Machine Learning 104

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

KDnuggets

NOVEMBER 6, 2019

Learn about statistical fallacies Data Scientists should avoid; New and quite amazing Deep Learning capabilities FB has been quietly open-sourcing; Top Machine Learning tools for Developers; How to build a Neural Network from scratch and more.

Statistics 49

Statistics Deep Learning Machine Learning 49

Analytics Vidhya

FEBRUARY 23, 2023

They collect, analyze, interpret data, and handle statistics, mathematics, and computer science. They are accountable for providing insights that go beyond statistical analyses. Introduction Data analysts with the technological know-how to tackle challenging problems are data scientists.

Statistics 280

Statistics Technology Analytics Deep Learning 280

Smart Data Collective

JUNE 10, 2022

The Bureau of Labor Statistics reports that there are over 105,000 data scientists in the United States. Machine Learning Engineer. As a machine learning engineer, you would create data funnels and deliver software solutions. Machine Learning Scientist. Are you interested in a career in data science?

Data Science 117

Data Science Machine Learning Statistics Business Intelligence 117

CIO Business Intelligence

JUNE 7, 2022

The chief aim of data analytics is to apply statistical analysis and technologies on data to find trends and solve problems. Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance.

Data Analytics 128

Data Analytics Diagnostic Analytics Management Analytics 128

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. business and quality rules, policies, statistical signals in the data, etc.).

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

datapine

MAY 14, 2019

2) “Deep Learning” by Ian Goodfellow, Yoshua Bengio and Aaron Courville. Best for: This best data science book is especially effective for those looking to enter the data-driven machine learning and deep learning avenues of the field. 4) “Machine Learning Yearning” by Andrew Ng.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 86

Metrics Machine Learning Risk Statistics 86

datapine

AUGUST 14, 2019

To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations. It helps to automate and makes the usage of the R programming statistical language easier and much more effective. perfect for statistical computing and design.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Birst BI

NOVEMBER 20, 2018

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. A foundational data analysis tool is Statistics , and everyone intuitively applies it daily. So, what do these terms really mean?

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84

CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. from 2022 to 2028.

Predictive Analytics 140

Predictive Analytics Analytics Predictive Modeling Forecasting 140

CIO Business Intelligence

OCTOBER 4, 2023

AI skills more valuable than certifications There were a couple of stand-outs among those. No obviously AI-related IT certifications made it onto Foote Partners’ list of highest payers, although the two-year-old IBM Certified Specialist — AI Enterprise Workflow V1 may make it to the top one day.

Prescriptive Analytics 125

Prescriptive Analytics IT Machine Learning Risk 125