ODSC - Open Data Science

APRIL 25, 2023

Hands-on Data-Centric AI: Data Preparation Tuning — Why and How? Be sure to check out her talk, “ Hands-on Data-Centric AI: Data preparation tuning — why and how? After all the data preparation is time to re-train our baseline model. Have we achieved the performance expected?

Data Preparation 52

Data Preparation Machine Learning Machine Learning AI 52

Pickl AI

OCTOBER 17, 2023

Learn how Data Scientists use ChatGPT, a potent OpenAI language model, to improve their operations. ChatGPT is essential in the domains of natural language processing, modeling, data analysis, data cleaning, and data visualization. It facilitates exploratory Data Analysis and provides quick insights.

Data Scientist 52

Data Scientist Machine Learning Machine Learning Data Analysis 52

Data Science Dojo

JUNE 7, 2023

The primary aim is to make sense of the vast amounts of data generated daily by combining statistical analysis, programming, and data visualization. It is divided into three primary areas: data preparation, data modeling, and data visualization.

Data Science 195

Data Science Data Visualization Data Scientist Machine Learning 195

KDnuggets

MARCH 9, 2020

Also: Linear to Logistic Regression, Explained Step by Step; Trends in Machine Learning in 2020; Tokenization and Text Data Preparation with TensorFlow & Keras; The Death of Data Scientists — will AutoML replace them?

Machine Learning 122

Machine Learning Machine Learning Data Preparation Data Scientist 122

Data Science Dojo

AUGUST 28, 2023

Similar to traditional Machine Learning Ops (MLOps), LLMOps necessitates a collaborative effort involving data scientists, DevOps engineers, and IT professionals. Some projects may necessitate a comprehensive LLMOps approach, spanning tasks from data preparation to pipeline production.

Exploratory Data Analysis 195

Exploratory Data Analysis Data Preparation Machine Learning Machine Learning 195

Data Science Dojo

APRIL 3, 2023

These tools provide a visual interface for building machine learning pipelines, making the process easier and more efficient for data scientists. These tools are designed to be user-friendly and do not require any coding skills, making it easier for data scientists to build models quickly and efficiently.

ML 195

ML ML Machine Learning Machine Learning 195

DataRobot

MARCH 25, 2019

Data scientist time is a precious, expensive commodity. Do you truly understand what your data science talent works on all day? Are they spending way too much time researching data science theory, coding the same data preparation tasks over and over again, and maintaining scripts for model factories?

Data Science 80

Data Science Data Scientist Data Preparation AI 80

Dataconomy

JULY 28, 2023

Data preprocessing ensures the removal of incorrect, incomplete, and inaccurate data from datasets, leading to the creation of accurate and useful datasets for analysis ( Image Credit ) Data completeness One of the primary requirements for data preprocessing is ensuring that the dataset is complete, with minimal missing values.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Dataconomy

JULY 10, 2023

Automation can be used to automate a number of tasks involved in decision-making, such as data collection, data preparation, and model deployment. Data science is a broader field that encompasses the collection, cleaning, analysis, and visualization of data.

Data Science 182

Data Science Machine Learning Machine Learning Data Scientist 182

Heartbeat

FEBRUARY 1, 2023

MLOps acts as the link between data scientists and the production team’s operations (a team consisting of machine learning engineers, software engineers, and IT operations professionals) as they work together to develop ML models and supervise the use of ML models in production. They might also help with data preparation and cleaning.

Machine Learning 96

Machine Learning Machine Learning Data Scientist ML 96

Pickl AI

FEBRUARY 21, 2023

Business organisations worldwide depend on massive volumes of data that require Data Scientists and analysts to interpret to make efficient decisions. Understanding the appropriate ways to use data remains critical to success in finance, education and commerce. What is Data Mining and how is it related to Data Science ?

Data Mining 52

Data Mining Data Mining Data Mining Data Scientist 52

IBM Data Science in Practice

JANUARY 9, 2024

By Carolyn Saplicki , IBM Data Scientist Industries are constantly seeking innovative solutions to maximize efficiency, minimize downtime, and reduce costs. All data scientists could leverage our patterns during an engagement. Industries that use air compressors include manufacturing, automotive, construction, and energy.

ML 130

ML ML AI AI 130

AWS Machine Learning Blog

FEBRUARY 6, 2024

Hugging Face integrates seamlessly with SageMaker, which is a fully managed service that enables developers and data scientists to build, train, and deploy ML models at scale. In this section, we describe the major steps involved in data preparation and model training.

AWS 97

AWS ML ML Data Preparation 97

AWS Machine Learning Blog

OCTOBER 5, 2023

We go through several steps, including data preparation, model creation, model performance metric analysis, and optimizing inference based on our analysis. We also go through best practices and optimization techniques during data preparation, model building, and model tuning.

Data Preparation 96

Data Preparation ML ML AWS 96

Dataconomy

SEPTEMBER 13, 2023

Data scientists dedicate a significant chunk of their time to data preparation, as revealed by a survey conducted by the data science platform Anaconda. This process involves rectifying or discarding abnormal or non-standard data points and ensuring the accuracy of measurements.

Machine Learning 195

Machine Learning Machine Learning AI AI 195

Tableau

FEBRUARY 24, 2021

Having had my own career shaped by the growth of data science, I wanted to dig into the questions of what data science is , what data science work is , and who data scientists are. Which leads to an important follow on: what exactly is data science work?

Data Science 96

Data Science Data Scientist Data Visualization Computer Science 96

Becoming Human

MAY 11, 2023

It covers everything from data preparation and model training to deployment, monitoring, and maintenance. The MLOps process can be broken down into four main stages: Data Preparation: This involves collecting and cleaning data to ensure it is ready for analysis.

Machine Learning 78

Machine Learning Machine Learning Cloud Computing DataOps 78

Towards AI

JUNE 27, 2023

The previous blog post, “Data Acquisition & Exploration: Exploring 5 Key MLOps Questions using AWS SageMaker”, explored how AWS SageMaker’s capabilities can help data scientists collaborate and accelerate data exploration and understanding. This section will focus on running transformations on our transaction data.

AWS 52

AWS Data Scientist Data Wrangling Data Preparation 52

Snorkel AI

NOVEMBER 9, 2023

As data science teams reorient around the enduring value of small, deployable models, they’re also learning how LLMs can accelerate data labeling. According to our poll participants, data preparation still occupies more data scientists’ hours than anything else. What is LLM distillation?

Data Scientist 59

Data Scientist Data Science AI AI 59

Snorkel AI

NOVEMBER 9, 2023

As data science teams reorient around the enduring value of small, deployable models, they’re also learning how LLMs can accelerate data labeling. According to our poll participants, data preparation still occupies more data scientists’ hours than anything else. What is LLM distillation?

Data Scientist 59

Data Scientist Data Science AI AI 59

KDnuggets

JULY 31, 2019

Learn the essential skills needed to become a Data Science rockstar; Understand CNNs with Python + Tensorflow + Keras tutorial; Discover the best podcasts about AI, Analytics, Data Science; and find out where you can get the best Certificates in the field.

Data Science 115

Data Science Analytics Analytics Data Scientist 115

DataRobot

DECEMBER 12, 2019

Back in 2012, Harvard Business Review called data scientists “the sexiest job of the 21st century.” That may or may not be true, but I do believe that one of the hardest jobs in the latter half of this decade is that of the executive responsible for developing and implementing AI strategy in the enterprise.

Data Preparation 19

Data Preparation Data Scientist AI AI 19

ODSC - Open Data Science

FEBRUARY 12, 2024

Most businesses already recognize the need to automate the actual analysis of data, but you can go further. Automating the data preparation and interpretation phases will take much time and effort out of the equation, too.

Augmented Analytics 98

Augmented Analytics Analytics Analytics Data Science 98

AWS Machine Learning Blog

AUGUST 4, 2023

Introducing Einstein Studio on Data Cloud Data Cloud is a data platform that provides businesses with real-time updates of their customer data from any touch point. With Einstein Studio, a gateway to AI tools on the data platform, admins and data scientists can effortlessly create models with a few clicks or using code.

AWS 73

AWS ML ML AI 73

Tableau

FEBRUARY 24, 2021

Having had my own career shaped by the growth of data science, I wanted to dig into the questions of what data science is , what data science work is , and who data scientists are. Which leads to an important follow on: what exactly is data science work?

Data Science 52

Data Science Data Scientist Data Visualization Computer Science 52

DataRobot

MARCH 2, 2021

We can help with data preparation and AI development, deployment, and monitoring. Monitoring deployed models is easy because we provide features to check on service health, data drift, and accuracy. They consulted with our data scientists and used the advanced capabilities available through our API to develop their AI solution.

AI 98

AI AI Data Scientist Data Preparation 98

IBM Journey to AI blog

AUGUST 11, 2023

Because the machine learning lifecycle has many complex components that reach across multiple teams, it requires close-knit collaboration to ensure that hand-offs occur efficiently, from data preparation and model training to model deployment and monitoring. Generative AI relies on foundation models to create a scalable process.

Data Science 58

Data Science Machine Learning Machine Learning ML 58

AWS Machine Learning Blog

DECEMBER 1, 2023

Launched in 2019, Amazon SageMaker Studio provides one place for all end-to-end machine learning (ML) workflows, from data preparation, building and experimentation, training, hosting, and monitoring. As a web application, SageMaker Studio has improved load time, faster IDE and kernel start up times, and automatic upgrades.

ML 96

ML ML Machine Learning Machine Learning 96

AWS Machine Learning Blog

FEBRUARY 22, 2023

This post is co-written with Swagata Ashwani, Senior Data Scientist at Boomi. First and foremost, Studio makes it easier to share notebook assets across a large team of data scientists like the one at Boomi. Swagata Ashwani is a Senior Data Scientist at Boomi with over 6+ years experience in Data Science.

AWS 70

AWS ML ML Data Science 70

AWS Machine Learning Blog

NOVEMBER 16, 2023

With SageMaker MLOps tools, teams can easily train, test, troubleshoot, deploy, and govern ML models at scale to boost productivity of data scientists and ML engineers while maintaining model performance in production.

AWS 89

AWS ML ML AI 89

Smart Data Collective

SEPTEMBER 16, 2020

However, many data scientists and business analysts can’t readily lean on automated regression techniques like logistic regression and linear regression. This stems, largely, from the fact that there are certain data regulations in place when it comes to marketing tech and predictive analytics software.

Predictive Analytics 119

Predictive Analytics Analytics Analytics Decision Trees 119

Iguazio

DECEMBER 14, 2023

Who This Book Is For This book is for practitioners in charge of building, managing, maintaining, and operationalizing the ML process end to end: Data science / AI / ML leaders: Heads of Data Science, VPs of Advanced Analytics, AI Lead etc. Exploratory data analysis (EDA) and modeling.

ML 52

ML ML Data Science Data Preparation 52

Precisely

FEBRUARY 12, 2024

Before business users can tap into the value of their data to deliver positive outcomes, that data must be complete, contextual, timely, accurate, and available. In other words, the data needs to be freed from its silos. Data scientists spend most of their time combining, harmonizing, and validating disparate data sets.

Data Governance 65

Data Governance Analytics Analytics Machine Learning 65

Heartbeat

JUNE 5, 2023

MLFlow From data preparation through application deployment, MLFlow is an open-source platform that manages the whole machine learning lifecycle. Aquarium Learning Aquarium Learning is a platform that allows data scientists and machine learning engineers to work together on complex data analysis tasks.

ML 59

ML ML Machine Learning Machine Learning 59

Dataconomy

MARCH 27, 2023

RPA uses a graphical user interface (GUI) to interact with applications and websites, while ML uses algorithms and statistical models to analyze data. On the other hand, ML requires a significant amount of data preparation and model training before it can be deployed.

ML 133

ML ML Machine Learning Machine Learning 133

Towards AI

JUNE 27, 2023

Its functionalities span from deep learning to text mining, data preparation, and predictive analytics, ensuring a versatile utility for developers and data scientists alike. RapidMiner RapidMiner, a renowned player in the realm of machine learning tools, offers an all-encompassing platform for a myriad of operations.

Machine Learning 95

Machine Learning Machine Learning ML ML 95

AWS Machine Learning Blog

MAY 23, 2023

Such a pipeline encompasses the stages involved in building, testing, tuning, and deploying ML models, including but not limited to data preparation, feature engineering, model training, evaluation, deployment, and monitoring. The following diagram illustrates the workflow.

Machine Learning 74

Machine Learning Machine Learning AWS ML 74