datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. offers many statistics and machine learning abilities.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 59

Data mining Machine Learning Deep Learning Marketing 59

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. Statistics developed in the last century are based on probability models (distributions). Data Has Properties. P >> N) ).

Statistics 145

Statistics Testing Predictive Modeling Modeling 145

O'Reilly on Data

MARCH 20, 2019

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

IBM Big Data Hub

FEBRUARY 14, 2024

Other uses include Netflix offering viewing recommendations powered by models that process data sets collected from viewing history; LinkedIn uses ML to filter items in a newsfeed, making employment recommendations and suggestions on who to connect with; and Spotify uses ML models to generate its song recommendations.

Cost-Benefit 89

Cost-Benefit Insurance Unstructured Data Machine Learning 89

IBM Big Data Hub

OCTOBER 16, 2023

Reinforcement learning uses ML to train models to identify and respond to cyberattacks and detect intrusions. Machine learning in financial transactions ML and deep learning are widely used in banking, for example, in fraud detection. Spotify uses ML models to generate its song recommendations.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

Smarten

APRIL 19, 2024

OpenAI – Azure OpenAI as the foundational entity for creating GPT models and is based on Large Language Models (LLM). GPT – Is based on a Large Language Model (LLM). Benefits include customized and optimized models, data, parameters and tuning. Open AI was developed by Microsoft.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

DataRobot Blog

DECEMBER 15, 2022

AI-powered Time Series Forecasting may be the most powerful aspect of machine learning available today. 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.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

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. However, the growing influence of ML isn’t without complications.

Machine Learning 82

Machine Learning Modeling Deep Learning Predictive Modeling 82

Domino Data Lab

APRIL 21, 2021

We’ll use a gradient boosting technique via XGBoost to create a model and I’ll walk you through steps you can take to avoid overfitting and build a model that is fit for purpose and ready for production. deep learning) there is no guaranteed explainability. Model training. Oversampling. fraud). ."

Statistics 69

Statistics Machine Learning Modeling Metrics 69

Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Model Drift. Models too, can drift and transform over time.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Domino Data Lab

AUGUST 1, 2021

In this article we cover explainability for black-box models and show how to use different methods from the Skater framework to provide insights into the inner workings of a simple credit scoring neural network model. The interest in interpretation of machine learning has been rapidly accelerating in the last decade.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

O'Reilly on Data

MARCH 24, 2020

In a world focused on buzzword-driven models and algorithms, you’d be forgiven for forgetting about the unreasonable importance of data preparation and quality: your models are only as good as the data you feed them. On the machine learning side, we are entering what Andrei Karpathy, director of AI at Tesla, dubs the Software 2.0

Machine Learning 346

Machine Learning Statistics Data Quality Modeling 346