Sisense

APRIL 10, 2020

We’ll actually do this later in this article. These support a wide array of uses, such as data analysis, manipulation, visualizations, and machine learning (ML) modeling. Some standard Python libraries are Pandas, Numpy, Scikit-Learn, SciPy, and Matplotlib. Modeling in R and Python. R libraries.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve.

Machine Learning 62

Machine Learning Data Science Statistics Deep Learning 62

Domino Data Lab

JULY 28, 2021

In this article, we will provide an overview of the three overlapping components of data science, the importance of communication and collaboration, and how the Domino Data Lab MLOps platform can help improve the speed and efficiency of your team. All models are not made equal. After cleaning, the data is now ready for processing.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI in commerce—such as models trained on inadequate or inappropriate data—lead to bad experiences that alienate consumers and businesses. AI models analyze vast amounts of data quickly and accurately.

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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

Smart Data Collective

SEPTEMBER 19, 2019

The Machine Learning Technology That Drives TTS. A couple of years ago, Medium contributor Utkarsh Saxena penned a great article on speech synthesis technology with machine learning. They talked about two very important machine learning approaches: Parametric TTS and Concatenative TTS.

Machine Learning 82

Machine Learning Technology Deep Learning Predictive Modeling 82

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.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Smarten

APRIL 19, 2024

In this article, we will discuss the current state of AI in analytics, as well as the future of this burgeoning industry and how it can be applied to analytics to simplify and clarify results and to make analytics easier for businesses and business users to leverage. GPT – Is based on a Large Language Model (LLM).

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Rocket-Powered Data Science

JULY 6, 2021

1) Automated Narrative Text Generation tools became incredibly good in 2020, being able to create scary good “deep fake” articles. 2) MLOps became the expected norm in machine learning and data science projects. the monitoring of very important operational ML characteristics: data drift, concept drift, and model security).

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

Domino Data Lab

APRIL 21, 2021

In this article, we’ll discuss the challenge organizations face around fraud detection, how machine learning can be used to identify and spot anomalies that the human eye might not catch. deep learning) there is no guaranteed explainability. It can be implemented as either unsupervised (e.g. Oversampling.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

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

Domino Data Lab

JULY 9, 2019

Assessing whether a business stakeholder is trying to solve for a problem that is descriptive, predictive, or prescriptive and then re-framing the problem as supervised learning, unsupervised learning, or reinforcement learning, respectively. This was one of several such articles, but that’s another talk.

Data Science 112

Data Science Machine Learning Advertising Modeling 112