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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

AUGUST 14, 2019

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

Data Science

Data Science Statistics Business Intelligence Visualization

Data science vs. machine learning: What’s the difference?

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 data science? What is machine learning?

Machine Learning

Machine Learning Data Science Statistics Deep Learning

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How to Optimize the Developer Experience for Monumental Impact

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Understanding User Needs and Satisfying Them

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Leading the Development of Profitable and Sustainable Products

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3 Key Components of the Interdisciplinary Field of Data Science

Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills.

Data Science

Data Science Statistics Recreation/Entertainment Predictive Analytics

Webinars

How to Optimize the Developer Experience for Monumental Impact

Generative AI Deep Dive: Advancing from Proof of Concept to Production

Understanding User Needs and Satisfying Them

Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Leading the Development of Profitable and Sustainable Products

MORE WEBINARS

11 most in-demand gen AI jobs companies are hiring for

CIO Business Intelligence

OCTOBER 13, 2023

Data scientist As companies embrace gen AI, they need data scientists to help drive better insights from customer and business data using analytics and AI. For most companies, AI systems rely on large datasets, which require the expertise of data scientists to navigate.

Deep Learning

Deep Learning Machine Learning Modeling Software

R vs Python: What’s the Best Language for Natural Language Processing?

Sisense

APRIL 10, 2020

In Talking Data , we delve into the rapidly evolving worlds of Natural Language Processing and Generation. Text data is proliferating at a staggering rate, and only advanced coding languages like Python and R will be able to pull insights out of these datasets at scale. NLP can be used on written text or speech data.

Deep Learning

Deep Learning Data Science Machine Learning Visualization

Of Muffins and Machine Learning Models

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning

Machine Learning Modeling Metadata Recreation/Entertainment

Leveraging user-generated social media content with text-mining examples

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Text representation In this stage, you’ll assign the data numerical values so it can be processed by machine learning (ML) algorithms, which will create a predictive model from the training inputs.

Data mining

Data mining Machine Learning Deep Learning Marketing

10 everyday machine learning use cases

IBM Big Data Hub

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

Machine Learning

Machine Learning Marketing Forecasting Modeling

The curse of Dimensionality

Domino Data Lab

OCTOBER 7, 2020

In this blog we show what the changes in behavior of data are in high dimensions. In our next blog we discuss how we try to avoid these problems in applied data analysis of high dimensional data. Data Has Properties. Statistics developed in the last century are based on probability models (distributions).

Statistics

Statistics Testing Predictive Modeling Modeling

Proposals for model vulnerability and security

O'Reilly on Data

MARCH 20, 2019

The objective here is to brainstorm on potential security vulnerabilities and defenses in the context of popular, traditional predictive modeling systems, such as linear and tree-based models trained on static data sets. It seems entirely possible to do the same with customer or transactional data.

Modeling

Modeling Machine Learning Predictive Modeling Consulting

Five machine learning types to know

IBM Big Data Hub

DECEMBER 20, 2023

What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. AI studio The post Five machine learning types to know appeared first on IBM Blog.

Machine Learning

Machine Learning Modeling Deep Learning Predictive Modeling

Credit Card Fraud Detection using XGBoost, SMOTE, and threshold moving

Domino Data Lab

APRIL 21, 2021

deep learning) there is no guaranteed explainability. In this blog post we will show an implementation of an ML-based anomaly detection based on XGBoost. We will go through a typical ML pipeline, where we do data ingestion, exploratory data analysis, feature engineering, model training and evaluation.

Statistics

Statistics Machine Learning Modeling Metrics

Better Forecasting with AI-Powered Time Series Modeling

DataRobot Blog

DECEMBER 15, 2022

Working from datasets you already have, a Time Series Forecasting model can help you better understand seasonality and cyclical behavior and make future-facing decisions, such as reducing inventory or staff planning. To accelerate the process, you can also increase the number of modeling workers (number of jobs running at the same time).

Forecasting

Forecasting Modeling ROI Machine Learning

The Cloud Connection: How Governance Supports Security

Alation

APRIL 14, 2022

The vision of big data freed organizations to capture more data sources at lower levels of detail and in vastly greater volumes. For example, data science always consumes “historical” data, and there is no guarantee that the semantics of older datasets are the same, even if their names are unchanged.

Metadata

Metadata Data Governance Modeling Data-driven

Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning. References.

Modeling

Modeling Deep Learning Machine Learning Knowledge Discovery

The unreasonable importance of data preparation

O'Reilly on Data

MARCH 24, 2020

Why is high-quality and accessible data foundational? The assumed value of data is a myth leading to inflated valuations of start-ups capturing said data. Generating data with a pre-specified analysis plan and running that analysis is good. Re-analyzing existing data is often very bad.”

Machine Learning

Machine Learning Statistics Data Quality Modeling

Data Leaders Brief

Top Data Science Tools That Will Empower Your Data Exploration Processes

Data science vs. machine learning: What’s the difference?

Webinars

Trending Sources

3 Key Components of the Interdisciplinary Field of Data Science

Webinars

11 most in-demand gen AI jobs companies are hiring for

R vs Python: What’s the Best Language for Natural Language Processing?

Of Muffins and Machine Learning Models

Leveraging user-generated social media content with text-mining examples

10 everyday machine learning use cases

The curse of Dimensionality

Proposals for model vulnerability and security

Five machine learning types to know

Credit Card Fraud Detection using XGBoost, SMOTE, and threshold moving

Better Forecasting with AI-Powered Time Series Modeling

The Cloud Connection: How Governance Supports Security

Explaining black-box models using attribute importance, PDPs, and LIME

The unreasonable importance of data preparation

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