IBM Big Data Hub

SEPTEMBER 6, 2023

AI used for content generation can save marketing teams time and money by creating blogs, marketing messages, copywriting materials, emails, subject lines, subtitles for videos, website copy and many other kinds of content aimed at a target audience.

Marketing 85

Marketing Technology Advertising ROI 85

Domino Data Lab

OCTOBER 7, 2020

MANOVA, for example, can test if the heights and weights in boys and girls is different. This statistical test is correct because the data are (presumably) bivariate normal. In this blog we show what the changes in behavior of data are in high dimensions. Statistical methods for analyzing this two-dimensional data exist.

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IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. This blog post will clarify some of the ambiguity. Machine learning is a subset of AI.

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DataRobot Blog

MAY 26, 2022

These methods provided the benefit of being supported by rich literature on the relevant statistical tests to confirm the model’s validity—if a validator wanted to confirm that the input predictors of a regression model were indeed relevant to the response, they need only to construct a hypothesis test to validate the input.

Risk 52

Risk Modeling Metrics Business Objectives 52

Insight

APRIL 9, 2019

NASA [Public domain] In this blog, I’ll discuss how I worked collaboratively with various domain experts, using reinforcement learning to develop innovative solutions in rocket engine development. The biggest categories of cost for hardware designers and manufacturers are testing, verification, and calibration of their control systems.

Manufacturing 75

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Domino Data Lab

JULY 28, 2021

Today, data is generated constantly through multiple channels including transactional systems, sensors, cameras, and online interactions. In fact, deep learning was first described theoretically in 1943. This includes accessing and preparing data, building and testing models and deploying them into production.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

CDW Research Hub

JULY 31, 2019

Recent advances in machine learning, and more specifically its subset, deep learning, have made it possible for computers to better understand natural language. These deep learning models can analyze large volumes of text and provide things like text summarization, language translation, context modeling, and sentiment analysis.

Deep Learning 49

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Insight

MAY 7, 2019

Here is another great blog post on BERT by a former Insight Fellow. BERT uses a deep bi-directional model using transformers. This API also takes an S3 bucket name as input and then performs inference on all inputs in the test file. The platform was tested on an Amazon p2.xlarge

Modeling 75

Modeling Testing Machine Learning Interactive 75

Cloudera

SEPTEMBER 12, 2018

Commonwealth Bank of Australia worked with Cloudera to implement a modern data platform with an AI-powered customer decisioning layer that dramatically improves how the bank interacts with its customers. Congratulations to the Sixth Annual Data Impact Awards winners appeared first on Cloudera Blog. Cloud Success: .

Machine Learning 44

Machine Learning Big Data Data Science Data Warehouse 44

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the other hand, sophisticated machine learning models are flexible in their form but not easy to control. This blog post motivates this problem more fully, and discusses monotonic splines and lattices as a solution. Curiosities and anomalies in your training and testing data become genuine and sustained loss patterns.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

CIO Business Intelligence

APRIL 15, 2022

MIT Technology Review has chronicled a number of failures, most of which stem from errors in the way the tools were trained or tested. In March 2016, Microsoft learned that using Twitter interactions as training data for machine learning algorithms can have dismaying results. In a statement on Oct. In a statement on Oct.

Analytics 143

Analytics Machine Learning Insurance Testing 143

Cloudera

NOVEMBER 3, 2021

Thanks to pioneers like Andrew NG and Fei-Fei Li, GPUs have made headlines for performing particularly well with deep learning techniques. Today, deep learning and GPUs are practically synonymous. While deep learning is an excellent use of the processing power of a graphics card, it is not the only use.

Deep Learning 115

Deep Learning Machine Learning Data Science Cost-Benefit 115

Domino Data Lab

AUGUST 10, 2021

PyTorch: used for deep learning models, like natural language processing and computer vision. It’s used for developing deep learning models. Horovod: is a distributed deep learning training framework that can be used with PyTorch, TensorFlow, Keras, and other tools.

Modeling 64

Modeling IT Risk Management Deep Learning 64

Smarten

APRIL 19, 2024

Vendors, service providers and analytics solution companies will package data products and design data management solutions to support business users in their interaction with suppliers, customers and stakeholders, and to inform and support customers and end users as they choose products and options.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

DataRobot Blog

FEBRUARY 2, 2023

These models are trained on massive amounts of text data using deep learning algorithms. As a result, they have the potential to revolutionize the way that we interact with machines and solve a wide range of machine learning problems. numpy()[idx] answer_end = (tf.argmax(output.end_logits, axis=1) + 1).numpy()[idx]

Modeling 52

Modeling Machine Learning Data Processing Interactive 52

IBM Big Data Hub

JANUARY 17, 2024

A chatbot is a program or script designed to interact and respond to humans in real-time conversation. AI-powered bots leverage machine learning and NLP ( natural language processing ) to understand prompts and context. They can learn from past interactions and improve over time.

Interactive 67

Interactive Sales Machine Learning Marketing 67

Insight

MARCH 25, 2020

In this blog, I will share how I built Pair , a scalable web application that takes in a product image, analyzes its design features using convolutional neural network, and recommends products in other categories with similar style elements. In this project, I was curious to see if deep learning approaches?—?specifically

Deep Learning 53

Deep Learning Metrics Data Processing Interactive 53

Sisense

AUGUST 6, 2020

AI and machine learning (ML) are not just catchy buzzwords; they’re vital to the future of our planet and your business. Be sure test cases represent the diversity of app users. As a product manager, you’ll want to do your own research to learn about the best modeling methods for your AI product domain and scenario.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Smart Data Collective

OCTOBER 14, 2019

Ludwig is a tool that allows people to build data-based deep learning models to make predictions. When Google talked about releasing this tool in its blog, the brand pointed out that if you don’t protect user data, you risk losing people’s trust. Here are some open-source options to consider. Kubernetes.

Data Science 68

Data Science Machine Learning Big Data Interactive 68

Alation

APRIL 14, 2022

Supports the ability to interact with the actual data and perform analysis on it. Automatic sampling to test transformation. They strove to ramp up skills in all manner of predictive modeling, machine learning, AI, or even deep learning. Subscribe to Alation's Blog. Pattern Matching. Visual Profiling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

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. IDEs (also sometimes referred to as notebooks) is a coding tool that makes it easier to develop and test code. Integrated Development Environments (IDEs). Contact us today.

Data Science 145

Data Science Visualization Modeling Enterprise 145

Domino Data Lab

MAY 8, 2019

Other good related papers include: “ Towards A Rigorous Science of Interpretable Machine Learning ”. Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Agile was originally about iterating fast on a code base and its unit tests, then getting results in front of stakeholders. 2018-06-21).

Machine Learning 105

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DataRobot Blog

DECEMBER 20, 2022

We’ll then empirically test this assumption based on an example of real estate asset assessment. Because our training dataset is multimodal and contains imagery data of residential properties in Madrid, DataRobot used machine learning models that contain deep learning based image featurizers.

Management 59

Management Machine Learning Optimization Modeling 59

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. show_in_notebook().

Modeling 139

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O'Reilly on Data

MARCH 24, 2020

For example, a pre-existing correlation pulled from an organization’s database should be tested in a new experiment and not assumed to imply causation [3] , instead of this commonly encountered pattern in tech: A large fraction of users that do X do Z. In particular, determining causation from correlation can be difficult.

Machine Learning 346

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