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 126

Data Science Machine Learning Predictive Modeling Experimentation 126

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

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 135

Data Analytics Diagnostic Analytics Management Analytics 135

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 105

Data Science Statistics Deep Learning Machine Learning 105

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

datapine

MAY 14, 2019

We gave you a curated list of our top 15 data analytics books , top 18 data visualization books , top 16 SQL books – and, as promised, we’re going to tell you all about the world’s best books on data science. 2) “Deep Learning” by Ian Goodfellow, Yoshua Bengio and Aaron Courville. click for book source**.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

Cloudera

FEBRUARY 25, 2021

Cloudera has a front-row seat to organizational challenges as those enterprises make Machine Learning a core part of their strategies and businesses. The work of a machine learning model developer is highly complex. We work with the largest companies in the world to help tackle their most challenging ML problems.

Deep Learning 82

Deep Learning Machine Learning Forecasting Visualization 82

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

Sisense

APRIL 10, 2020

R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. It’s quite popular for its visualizations: charts, graphs, pictures, and various plots. These visualizations are useful for helping people visualize and understand trends , outliers, and patterns in data.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Domino Data Lab

JULY 28, 2021

Through a marriage of traditional statistics with fast-paced, code-first computer science doctrine and business acumen, data science teams can solve problems with more accuracy and precision than ever before, especially when combined with soft skills in creativity and communication. Math and Statistics Expertise.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

Analytics Vidhya

FEBRUARY 24, 2021

ArticleVideo Book Introduction to Artificial Intelligence and Machine Learning Artificial Intelligence (AI) and its sub-field Machine Learning (ML) have taken the world by storm. The post A Comprehensive Step-by-Step Guide to Become an Industry Ready Data Science Professional appeared first on Analytics Vidhya.

Data Science 307

Data Science Machine Learning Analytics IT 307

Smart Data Collective

SEPTEMBER 16, 2020

These statistical models are growing as a result of the wide swaths of available current data as well as the advent of capable artificial intelligence and machine learning. Deep Learning, Machine Learning, and Automation. From a predictive analytics standpoint, you can be surer of its utility.

Predictive Analytics 122

Predictive Analytics Analytics Predictive Modeling Data mining 122

IBM Big Data Hub

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

Data Science 57

Data Science Machine Learning Cost-Benefit Deep Learning 57

Analytics Vidhya

FEBRUARY 4, 2022

Overview Motivation to Learn R Covering the BASICS & MUST KNOW Concepts in R Introduction Since you are reading this article, I am assuming that right now you are in your journey of becoming a data scientist. There is a high possibility that you already are aware of some of the data visualization and analytics […].

Visualization 239

Visualization Analytics Deep Learning Statistics 239

Analytics Vidhya

NOVEMBER 6, 2020

Introduction to Artificial Intelligence and Machine Learning Artificial Intelligence (AI) and its sub-field Machine Learning (ML) have taken the world by storm. The post A Comprehensive Step-by-Step Guide to Become an Industry-Ready Data Science Professional appeared first on Analytics Vidhya.

Data Science 254

Data Science Machine Learning Analytics IT 254

Domino Data Lab

JULY 28, 2021

Data science is a field at the convergence of statistics, computer science and business. In this article, take a deep dive into data science and how Domino’s Enterprise MLOps platform allows you to scale data science in your business. In fact, deep learning was first described theoretically in 1943.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

FineReport

DECEMBER 19, 2019

At the same time, it also advocates visual exploratory analysis. The visualization component library of FineReport is very rich. Pandas incorporates a large number of analysis function methods, as well as common statistical models and visualization processing. It is recommended that everyone learn to learn.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. Within DataRobot, each model created in the model leaderboard contains a feature impact visualization, which makes use of a mathematical technique called permutation importance to measure variable importance.

Risk 52

Risk Modeling Metrics Business Objectives 52

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 81

Machine Learning Modeling Deep Learning Predictive Modeling 81

bridgei2i

OCTOBER 7, 2020

Underwriting essentially means evaluating the risk proposition of an insurance cover and determining how much an insurer should charge for the same by studying historical data and statistical models. An underwriter typically navigates this process by drawing on their experience and information gathered from various unstructured sources.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

Business Over Broadway

SEPTEMBER 5, 2018

Check out these links to get you started: UN Data from the United Nations Statistics Division. Using machine learning, deep learning, and visual recognition to improve critical processes. If you understand the data, you understand the process that generates them. UN Sustainable Development Goals Indicators.

Data Science 57

Data Science Statistics Advertising Deep Learning 57

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. While AGI promises machine autonomy far beyond gen AI, even the most advanced systems still require human expertise to function effectively.

Cost-Benefit 95

Cost-Benefit Modeling Manufacturing Interactive 95

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

Domino Data Lab

JULY 22, 2019

why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”. He was saying this doesn’t belong just in statistics. It’s not going to happen.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Analytics Vidhya

FEBRUARY 28, 2023

Introduction Data science has taken over all economic sectors in recent times. To achieve maximum efficiency, every company strives to use various data at every stage of its operations.

Data Science 325

Data Science Big Data Analytics IT 325

Analytics Vidhya

DECEMBER 13, 2021

Introduction 2021 is a year that proved nothing is better than a Proof of Work to evaluate any candidate’s worth, initiative, and skill. Pursuing any data science project will help you polish your resume. These projects will not only deepen an understanding of the concepts but also, help you gain some practical experience in the […].

Data Science 333

Data Science Analytics Data mining Deep Learning 333

Smarten

APRIL 19, 2024

The Current State of AI in Analytics By combining machine learning with AI, analytics vendors can and have made strides in providing user-friendly, self-serve augmented analytics products that include the newest versions of these technologies: Machine Learning (ML) Generative Artificial Intelligence (GenAI) Deep Learning Natural Language Processing (..)

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

DataRobot

NOVEMBER 9, 2021

Signal classification models are typically built using time series principles; traditionally used features that include central, windowed, lag, and lead statistics can do the job but sometimes there might be scenarios where we want to eke out more performance out of the data. Image courtesy towardsAI. See DataRobot in Action.

Visualization 52

Visualization Unstructured Data Statistics Metrics 52

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

IBM Big Data Hub

OCTOBER 12, 2023

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. Due to deep learning and other advancements, the field of AI remains in a constant and fast-paced state of flux.

Machine Learning 73

Machine Learning Deep Learning Interactive Modeling 73

datapine

NOVEMBER 19, 2019

Exciting and futuristic, the concept of computer vision is based on computing devices or programs gaining the ability to extract detailed information from visual images. Visual analytics: Around three million images are uploaded to social media every single day. Artificial Intelligence (AI).

Technology 279

Technology Internet of Things IT IoT 279

Domino Data Lab

MAY 8, 2019

I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Not yet, if ever.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

O'Reilly on Data

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. As statistics and related techniques become more important in software development, more programmers are encountering stats in programming classes.

Data-driven 335

Data-driven Software Statistics Marketing 335

KDnuggets

SEPTEMBER 17, 2019

We identify two main groups of Data Science skills: A: 13 core, stable skills that most respondents have and B: a group of hot, emerging skills that most do not have (yet) but want to add. See our detailed analysis.

Data Science 123

Data Science Deep Learning Statistics Machine Learning 123

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

CONTACT Software

FEBRUARY 19, 2019

In line with this, Gartner has now published a “ Magic Quadrant for Data Science and Machine Learning Platforms “ The document itself can only be viewed behind a paywall, but on the net some of the companies mentioned in the report offer access to the document by entering the address.

Data Science 40

Data Science Statistics Machine Learning Deep Learning 40

Domino Data Lab

JULY 15, 2021

Originally created for software development, Python is used in a variety of contexts, including deep learning research and model deployment. RStudio is an IDE for the R language used primarily for statistical analysis as well as data visualization. Some common IDEs are RStudio and Jupyter Notebook.

Data Science 145

Data Science Visualization Modeling Enterprise 145