DataRobot

FEBRUARY 10, 2021

Machine learning is a glass cannon. The promise and power of AI lead many researchers to gloss over the ways in which things can go wrong when building and operationalizing machine learning models. As a data scientist, one of my passions is to reproduce research papers as a learning exercise.

Modeling 98

Modeling Deep Learning Machine Learning Testing 98

Insight

SEPTEMBER 20, 2019

Segmentation Since a few patients had multiple images in the dataset, the data were separated, by patient, into three parts: training (80%), validation (10%), and testing (10%). The box plot below shows a summary of the testing results. This shows that the model indeed learned where and what to look for in the images.

Deep Learning 53

Deep Learning Cost-Benefit Testing Modeling 53

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

Data Science 101

MAY 20, 2019

The exam can be broken down into 4 components: Machine Learning, Azure ML Studio, Azure Products, and Python. Machine Learning. These are topics which would be covered in a traditional machine learning course. Scikit-learn Azure Machine Learning SDK for Python Hyperparameters.

Data Science 111

Data Science Machine Learning Deep Learning Testing 111

IBM Big Data Hub

JULY 11, 2023

Better machine learning (ML) algorithms, more access to data, cheaper hardware and the availability of 5G have contributed to the increasing application of AI in the healthcare industry, accelerating the pace of change. Another published study found that AI recognized skin cancer better than experienced doctors.

Deep Learning 60

Deep Learning Cost-Benefit Insurance Machine Learning 60

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

Management 332

Management Machine Learning Experimentation Metrics 332

Smart Data Collective

FEBRUARY 20, 2022

With these tools, your SaaS can: Merge and improve the application code constantly Automate the development, testing, and release of software Integrate operations and developer workflows And much more. AWS also offers developers the technology to develop smart apps using machine learning and complex algorithms.

Cost-Benefit 116

Cost-Benefit Data Lake Software Machine Learning 116

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. In doing so, I’ll demonstrate the application of ML techniques to the manufacturing industry and the role of the Machine Learning Product Manager.

Manufacturing 75

Manufacturing Machine Learning Testing Software 75

Smart Data Collective

JULY 30, 2020

In December, Springer published an insightful article about the value of deep learning for VPNs. The article “Deep learning-based real-time VPN encrypted traffic identification methods” delves into the use of machine learning to improve encryption models. It is also used for testing more effectively.

Machine Learning 86

Machine Learning Testing Deep Learning Advertising 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

Cloudera

APRIL 27, 2023

This is enabled through a Ray Module in cmlextensions python package published by our team. Its innovative architecture enables seamless integration with ML and deep learning libraries like TensorFlow and PyTorch. To make it easier for CML users to leverage Ray, Cloudera has published a Python package called CMLextensions.

Machine Learning 79

Machine Learning Dashboards Deep Learning Testing 79

Insight

MAY 16, 2019

It is a high-level, multifaceted field that allows machines to iteratively learn and understand complex representations from images and videos to automate human visual tasks. How Deep Learning scales based on the amount of Data [Copyright: Andrew Ng ]. Transfer Learning?—?YOLO. Precision?—?Recall

Deep Learning 84

Deep Learning Machine Learning Metadata Data Science 84

Insight

MAY 7, 2019

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 The dataset contains 25,000 reviews for training and 25,000 for testing. Batch Inference ?—?This To support GPU training, Nvidia Docker 2 was used.

Modeling 75

Modeling Testing Machine Learning Interactive 75

Cloudera

SEPTEMBER 12, 2018

The week is typically filled with exciting announcements from Cloudera and many partners and others in the data management, machine learning and analytics industry. Enterprise Machine Learning: . It’s a big week for us, as many Clouderans descend on New York for the Strata Data Conference. Cloud Success: .

Machine Learning 45

Machine Learning Big Data Data Science Data Warehouse 45

Smart Data Collective

SEPTEMBER 9, 2019

The majority of machine learning and deep learning solutions have focused on fundamental analysis of securities. However, deep learning and other artificial intelligence technologies will also change the future of technical analysis as well. New developments in deep learning with technical analysis.

Deep Learning 66

Deep Learning Forecasting Machine Learning Strategy 66

Cloudera

SEPTEMBER 11, 2020

Due to COVID-19, retailers world-wide had their e-commerce capabilities put to the test with entire countries being in lockdown for weeks, even months, due to the pandemic. . What they have learned is that often their legacy Machine Learning models (e.g. Data and analytics.

Manufacturing 92

Manufacturing Forecasting Digital Transformation Sales 92

Domino Data Lab

AUGUST 9, 2021

With the right tools, your data science teams can focus on what they do best – testing, developing and deploying new models while driving forward-thinking innovation. Before selecting a tool, you should first know your end goal – machine learning or deep learning. This is no exaggeration by any means.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

DataRobot Blog

MARCH 9, 2022

This article was originally published at Algorithimia’s website. With that said, recent advances in deep learning methods have allowed models to improve to a point that is quickly approaching human precision on this difficult task. The company was acquired by DataRobot in 2021. Find out more about DataRobot MLOps here.

Machine Learning 52

Machine Learning Deep Learning Modeling Measurement 52

Domino Data Lab

APRIL 3, 2019

Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. That presented an opportunity to learn, putting me in the same position as much of the audience. Newer work in machine learning (e.g., We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

CIO Business Intelligence

APRIL 15, 2022

And 20% of IT leaders say machine learning/artificial intelligence will drive the most IT investment. Insights gained from analytics and actions driven by machine learning algorithms can give organizations a competitive advantage, but mistakes can be costly in terms of reputation, revenue, or even lives.

Analytics 145

Analytics Machine Learning Insurance Testing 145

Smarten

APRIL 19, 2024

The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. Nothing…and I DO mean NOTHING…is more prominent in technology buzz today than Artificial Intelligence (AI). billion, with the market growing by 31.1%

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

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 119

Deep Learning Machine Learning Data Science Cost-Benefit 119

Insight

JANUARY 14, 2020

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. And the winner is… Both implementations of our gym equipment classifier achieved 99% accuracy on the test set. Check out the Keras documentation here.

Metrics 58

Metrics Optimization Modeling Testing 58

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is now able to automatically create and maintain materialized views and then transparently rewrite queries to use the materialized views using the machine-learned automated materialized view autonomics feature in Amazon Redshift. The test includes the 99 TPC-DS SELECT queries.

Data Warehouse 93

Data Warehouse Cost-Benefit Dashboards Optimization 93

Domino Data Lab

AUGUST 10, 2021

At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. PyTorch: used for deep learning models, like natural language processing and computer vision. It’s used for developing deep learning models.

Modeling 64

Modeling IT Risk Management Deep Learning 64

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

Domino Data Lab

MARCH 29, 2021

The addition of the MLlib library, consisting of common learning algorithms and utilities, opened up Spark for a wide range of machine learning tasks and paved the way for running complex machine learning workflows on top of Apache Spark clusters. A benchmark published by Nvidia shows 3.8x as the base image.

Cost-Benefit 98

Cost-Benefit Machine Learning Testing Interactive 98

BizAcuity

MARCH 31, 2022

There have been so many articles published about AI and its applications, you can find millions of articles from broad concepts to deep technical literature on the internet. More use-cases are being tried, tested and built everyday, the innovation in this field will not cease for the next few years. Applications of AI.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

Data Science and Beyond

OCTOBER 15, 2017

To answer the question, here are some posts on things I’ve done: Joined Automattic by improving the Elasticsearch language detection plugin , calculated customer lifetime value , analysed A/B test results , built recommender systems (including one for Bandcamp music ), competed on Kaggle , and completed a PhD. I’m pretty busy.

Data Science 71

Data Science Deep Learning Machine Learning Data-driven 71

Insight

MARCH 25, 2020

After reading this, I hope you can learn how to build deep learning models using TensorFlow Keras, productionalize the model as a Streamlit app, and deploy it as a Docker container on Google Cloud Platform (GCP) using Google Kubernetes Engines (GKE). In this project, I was curious to see if deep learning approaches?—?specifically

Deep Learning 53

Deep Learning Metrics Data Processing Interactive 53

Insight

FEBRUARY 13, 2019

He is currently a machine learning engineer at Casetext where he works on natural language processing for the legal industry. In late 2018, Google open-sourced BERT, a powerful deep learning algorithm for natural language processing. Prior to Insight, he was at IBM Watson. Yay this is fun! Run training.

Testing 72

Testing Machine Learning Deep Learning Modeling 72

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. We had big surprises at several turns and have subsequently published a series of reports. In order, those are: “5 findings from O’Reilly’s machine learning adoption survey companies should know”. “

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

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. Launchpad: Allows you to publish your deployed models in different formats.

Data Science 145

Data Science Visualization Modeling Enterprise 145

DataRobot

NOVEMBER 9, 2021

“One look is worth a Thousand Words” This phrase was used in 1913 to convey that graphics had a place in newspaper publishing. 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. . Image courtesy towardsAI.

Visualization 52

Visualization Unstructured Data Statistics Metrics 52

Domino Data Lab

JULY 9, 2019

Wiggins advocated that data scientists find problems that impact the business; re-frame the problem as a machine learning (ML) task; execute on the ML task; and communicate the results back to the business in an impactful way. I still believe that data science is the craft of trying to apply machine learning to some real world problem.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

JANUARY 25, 2021

This study is based on title usage on O’Reilly online learning. The data includes all usage of our platform, not just content that O’Reilly has published, and certainly not just books. It’s particularly difficult if testing includes issues like fairness and bias. AI, Machine Learning, and Data.

Machine Learning 363

Machine Learning Software Testing Technology 363

Occam's Razor

OCTOBER 12, 2017

The first two are from editions of my newsletter, The Marketing – Analytics Intersect (it goes out weekly, and is now my primary publishing channel, sign up!). When you go to the interview, the hiring company will proceed to ask questions that test your competency in the listed job requirements. Intro to Machine Learning.

Marketing 136

Marketing Analytics Machine Learning Strategy 136