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

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. . Meta-Orchestration .

Testing 307

Testing Machine Learning Consulting Data Quality 307

Business Over Broadway

DECEMBER 20, 2018

The importance of data science and machine learning continues to grow in business and beyond. Favorite Data Science and Machine Learning Blogs, Podcasts and Newsletters – In a worldwide survey, over 16,000 data professionals were asked to indicate their favorite data science blogs, podcasts and newsletters.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74

Corinium

JUNE 6, 2019

A playbook for this is to run multiple experiments in parallel and create ‘MVPs’ (fail/learn fast), as well as incorporate feedback mechanisms to enable an improvement loop, and scaling the ones that show the fastest path to ROI. What advances do you see in Visual Analytics in the next five years?

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

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. Here’s a preview of what you can leverage with one click in CML: Deep Learning for Anomaly Detection.

Deep Learning 83

Deep Learning Machine Learning Forecasting Visualization 83

Smart Data Collective

JULY 1, 2023

Image annotation is the act of labeling images for AI and machine learning models. The resulting structured data is then used to train a machine learning algorithm. There are a lot of image annotation techniques that can make the process more efficient with deep learning.

Metrics 64

Metrics Machine Learning Uncertainty Deep Learning 64

Sisense

APRIL 10, 2020

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. These support a wide array of uses, such as data analysis, manipulation, visualizations, and machine learning (ML) modeling.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Smarten

APRIL 19, 2024

Anomaly Alerts KPI monitoring and Auto Insights allows business users to quickly establish KPIs and target metrics and identify the Key Influencers and variables for the target KPI.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

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 59

Data Science Machine Learning Cost-Benefit Deep Learning 59

DataRobot

OCTOBER 20, 2021

Data literacy is the ability to understand data science and AI applications critically using basic data visualization, communication, and reasoning skills. data engineers, data scientists, machine learning engineers, etc.) rule-based AI , machine learning , deep learning , etc.) What Is Data Literacy?

Machine Learning 52

Machine Learning Metrics Risk Deep Learning 52

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.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

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

SEPTEMBER 9, 2019

Data science teams in industry must work with lots of text, one of the top four categories of data used in machine learning. Next let’s use the displaCy library to visualize the parse tree for that sentence: In [4]: from spacy import displacy?? Usually it’s human-generated text, but not always. part of speech.

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110

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

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

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

AWS Big Data

JUNE 26, 2023

These techniques utilize various machine learning (ML) based approaches. We use Amazon Neptune to visualize the customer data before and after the merge and harmonization. Run Steps 1–5 in the notebook to analyze and visualize the raw insurance data. Jupyter notebooks are web-based interactive platforms.

Insurance 77

Insurance Visualization Data Lake Metrics 77

Insight

MARCH 4, 2020

In this blog, I’ll describe how to solve this with Contextual Topic Identification, leveraging machine learning methods to identify semantically similar groups and surface relevant category tags of the reviews. Let’s do a quick deep dive into the model design. Below is the result, where clusters are balanced and quite separated.

Visualization 81

Visualization Modeling Metrics Measurement 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. What is machine learning?

Machine Learning 82

Machine Learning Modeling Deep Learning Predictive Modeling 82

Grooper

AUGUST 19, 2019

An interview with Pranshuk Kathed, machine and deep learning enthusiast. For simple reporting projects, I might spend 8 hours getting the right data and then just a couple of hours producing the needed visualizations. What are the metrics that business wants to see and why it is valuable? What is machine learning?

Machine Learning 40

Machine Learning Metrics Descriptive Analytics Testing 40

Domino Data Lab

JULY 28, 2021

Communication cannot be emphasized enough, for it is this trait that ensures results are effectively translated from the white board to impact on business metrics. In fact, deep learning was first described theoretically in 1943. The most commonly used techniques today are under the umbrella of machine learning.

Data Science 45

Data Science Machine Learning Statistics Deep Learning 45

Cloudera

SEPTEMBER 20, 2022

A “comic book” in this context is a story told visually through a series of images, and optionally (though often) in conjunction with written language, e.g., in speech bubbles or as captions. Deep learning models are data hungry, and state-of-the-art systems like DALL·E 2 are trained with massive data sets of images scraped from the internet.

Deep Learning 86

Deep Learning Cost-Benefit Risk Data-driven 86

Insight

OCTOBER 25, 2019

Image credit: [link] As the title suggests, this is a story about a question that may resonate well with many machine learning practitioners trying to build applications in the real world, where clean and annotated data on a specific problem can be sparse— How do we leverage the power of AI when we have very little data?

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). What metrics are used to evaluate success? Introduction.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

DataRobot Blog

APRIL 22, 2022

In our previous post , we talked about how red AI means adding computational power to “buy” more accurate models in machine learning , and especially in deep learning. We covered different ways of measuring model efficiency and showed ways to visualize this and select models based on it. Conclusion.

Machine Learning 98

Machine Learning Measurement Deep Learning Manufacturing 98

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 also really informed a lot of the early thinking about data visualization.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

AUGUST 29, 2019

This article provides an excerpt “Deep Reinforcement Learning” from the book, Deep Learning Illustrated by Krohn , Beyleveld , and Bassens. The article includes an overview of reinforcement learning theory with focus on the deep Q-learning. Essential Theory of Reinforcement Learning.

Optimization 111

Optimization Modeling Deep Learning Metrics 111

Insight

JANUARY 14, 2020

CNNs have been widely considered state-of-the-art tools for computer vision since 2012, when AlexNet won the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Keras is an open source deep learning API that was written in Python and runs on top of Tensorflow, so it’s a little more user-friendly and high-level than Tensorflow.

Metrics 58

Metrics Optimization Modeling Testing 58

Insight

MARCH 28, 2019

Visualize Glassdoor reviews from your dream companies Yanxia Li built CompanySnapshot, a tool to help individuals visualize Glassdoor employee reviews, reducing the time needed to thoroughly review a company’s Glassdoor profile. xPea allows users to discover these and other surprising matches as they search for their dream jobs.

Dashboards 70

Dashboards Visualization Data Science Machine Learning 70

DataRobot

NOVEMBER 9, 2021

When we convert the single channel audio signal time series into an energy spectrogram, it allows us to run state of the art deep learning architectures on the image. . DataRobot’s Visual AI models in autopilot built a model with an improved 1 percent better performance without any additional parameter tuning.

Visualization 52

Visualization Unstructured Data Statistics Metrics 52

DataRobot Blog

DECEMBER 20, 2022

DataRobot also processes nearly every type of data , such as satellite and street imagery of real estate properties using DataRobot Visual AI , the latitude and longitude of properties and nearby city’s points of interest using DataRobot Location AI , tweets, and reviews with geotagged locations using DataRobot Text AI.

Management 59

Management Machine Learning Optimization Modeling 59