Unite.AI

MAY 6, 2024

As an AI-powered Digital Engineering enterprise, Persistent has embraced GenAI to revolutionize various aspects of the software engineering lifecycle. Data Quality and Bias: The quality and representativeness of data used to train the AI model have a significant impact on its output.

Automation 147

Automation Software Engineer Generative AI Software Development 147

Unite.AI

DECEMBER 13, 2024

Prior to Yanolja, Junyoung had a distinguished career at Google, where he worked for nearly two decades in various roles, including Software Engineer, Engineering Manager, and Engineering Director. AI is poised to revolutionize the travel industry by unlocking the vast potential of underutilized data.

Software Engineer 100

Software Engineer Data Quality Data Platform Automation 100

The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

Machine Learning Metadata Data Scientist Data Quality 134

Towards AI

MAY 20, 2023

Challenges of building custom LLMs Building custom Large Language Models (LLMs) presents an array of challenges to organizations that can be broadly categorized under data, technical, ethical, and resource-related issues. Acquiring a significant volume of domain-specific data can be challenging, especially if the data is niche or sensitive.

LLM 98

LLM Large Language Models Chatbots Natural Language Processing 98

Unite.AI

JUNE 24, 2024

It’s been fascinating to see the shifting role of the data scientist and the software engineer in these last twenty years since machine learning became widespread. Astro provides robust data-centric alerting with customizable notifications that can be sent through various channels like Slack and PagerDuty.

Data Scientist 130

Data Scientist Large Language Models Machine Learning Software Engineer 130

Marktechpost

FEBRUARY 8, 2025

Code generation models have made remarkable progress through increased computational power and improved training data quality. These models undergo pre-training and supervised fine-tuning (SFT) using extensive coding data from web sources. State-of-the-art models like Code-Llama, Qwen2.5-Coder,

Automation 52

Automation Large Language Models Data Quality Conversational AI 52

ODSC - Open Data Science

FEBRUARY 24, 2023

Data Quality Now that you’ve learned more about your data and cleaned it up, it’s time to ensure the quality of your data is up to par. With these data exploration tools, you can determine if your data is accurate, consistent, and reliable.

Data Analysis 126

Data Analysis Data Science Business Intelligence Python 126

AWS Machine Learning Blog

AUGUST 29, 2023

The batch inference pipeline includes steps for checking data quality against a baseline created by the training pipeline, as well as model quality (model performance) if ground truth labels are available. If the batch inference pipeline discovers data quality issues, it will notify the responsible data scientist via Amazon SNS.

Data Scientist 90

Data Scientist Data Quality Python ML 90

Pickl AI

DECEMBER 4, 2024

Data Wrangling The process of cleaning and preparing raw data for analysis—often referred to as “ data wrangling “—is time-consuming and requires attention to detail. Ensuring data quality is vital for producing reliable results. business analysts, software engineers).

Data Science 52

Data Science Data Scientist Software Engineer Continuous Learning 52

ODSC - Open Data Science

SEPTEMBER 27, 2023

Relational Databases Some key characteristics of relational databases are as follows: Data Structure: Relational databases store structured data in rows and columns, where data types and relationships are defined by a schema before data is inserted.

Big Data 98

Big Data Metadata ETL Data Science 98

Flipboard

JULY 31, 2023

Simultaneously, businesses harness its potential to engineer products that hinge on image recognition, including image search engines, autonomous vehicles, and facial recognition software. This powerful dataset has over 330,000 images, each annotated with 80 object categories and 5 captions describing the scenes.

Machine Learning 123

Machine Learning Computer Vision Deep Learning Convolutional Neural Networks 123

Google Research AI blog

MARCH 27, 2023

Posted by Rahul Goel and Aditya Gupta, Software Engineers, Google Assistant Virtual assistants are increasingly integrated into our daily routines. Additional details on data quality, data collection methodology, and modeling experiments can be found in our paper.

NLP 98

NLP Natural Language Processing Software Engineer Data Quality 98

AWS Machine Learning Blog

MARCH 28, 2024

Preprocessing – You might consider a series of preprocessing steps to improve data quality and training efficiency. For example, certain data sources can contain a fair number of noisy tokens; deduplication is considered a useful step to improve data quality and reduce training cost.

Large Language Models 123

Large Language Models LLM Machine Learning Generative AI 123

AWS Machine Learning Blog

APRIL 26, 2023

Ensuring data quality, governance, and security may slow down or stall ML projects. He has a background in software engineering and AI research. You may often select low-value use cases as proof of concept rather than solving a meaningful business or customer problem. Connect with him on LinkedIn.

ML 113

ML Machine Learning Data Science Data Drift 113

ODSC - Open Data Science

OCTOBER 25, 2024

By leveraging Delphina, teams can significantly reduce the manual work required to set prices, optimize supply chains, prevent fraud, or personalize products, all while keeping data scientists in the driver’s seat, ensuring efficiency without sacrificing control.

Data Scientist 52

Data Scientist Software Engineer Machine Learning Automation 52

AWS Machine Learning Blog

MARCH 9, 2023

As machine learning (ML) models have improved, data scientists, ML engineers and researchers have shifted more of their attention to defining and bettering data quality. This has led to the emergence of a data-centric approach to ML and various techniques to improve model performance by focusing on data requirements.

ML Engineer 93

ML Engineer Data Scientist Convolutional Neural Networks ML 93

Towards AI

AUGUST 16, 2023

Data quality: ensuring the data received in production is processed in the same way as the training data. Models fail over time: Models fail for inexplicable reasons (system failure, bad network connection, system overload, bad input or corrupted request), so detecting the root cause early or its frequency is important.

Machine Learning 98

Machine Learning Software Development Data Drift Data Science 98

ODSC - Open Data Science

OCTOBER 21, 2024

Gain practical insights on building robust AI strategies, implementing data cultures centered on reliability and trust, and effectively managing data incidents that could impact your AI products. This session covers essential considerations such as data quality, scalability, contextual relevance, and permission-aware AI systems.

Generative AI 52

Generative AI Large Language Models Data Science Software Engineer 52

Pickl AI

JULY 25, 2023

Data Integration and ETL (Extract, Transform, Load) Data Engineers develop and manage data pipelines that extract data from various sources, transform it into a suitable format, and load it into the destination systems. They establish data governance processes to maintain the accuracy and reliability of data.

Data Science 52

Data Science Data Scientist ETL Machine Learning 52

Snorkel AI

FEBRUARY 2, 2023

Scenario: Entity linking with payroll data and job classifications I’m building an entity-linking app to connect job listings in a payroll system to a job categorization system developed by the Bureau of Labor Statistics. I thumb through the data and look for patterns. We’ll receive two datasets: The job listings in the payroll system.

Auto-classification 52

Auto-classification Software Engineer Neural Network Machine Learning 52

Snorkel AI

FEBRUARY 2, 2023

Scenario: Entity linking with payroll data and job classifications I’m building an entity-linking app to connect job listings in a payroll system to a job categorization system developed by the Bureau of Labor Statistics. I thumb through the data and look for patterns. We’ll receive two datasets: The job listings in the payroll system.

Auto-classification 52

Auto-classification Software Engineer Neural Network Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 16, 2023

Data Management – Efficient data management is crucial for AI/ML platforms. Regulations in the healthcare industry call for especially rigorous data governance. It should include features like data versioning, data lineage, data governance, and data quality assurance to ensure accurate and reliable results.

Data Scientist 115

Data Scientist ML Data Science Machine Learning 115

Viso.ai

SEPTEMBER 2, 2024

Verifying and validating annotations to maintain high data quality and reliability. Good understanding of spatial data, 2D and 3D geometry, and coordinate systems. So, you have to specialize in some of the related areas: image annotation, image/video processing, software engineering, etc.

Computer Vision 52

Computer Vision Software Engineer Convolutional Neural Networks Neural Network 52

ODSC - Open Data Science

FEBRUARY 11, 2025

While machine learning engineers focus on building models, AI engineers often work with pre-trained foundation models, adapting them to specific use cases. This shift has made AI engineering more multidisciplinary, incorporating elements of data science, software engineering, and systemdesign.

AI Engineer 52

AI Engineer Machine Learning Software Engineer Prompt Engineering 52

Pickl AI

OCTOBER 2, 2024

Summary: Artificial Intelligence (AI) is revolutionising Genomic Analysis by enhancing accuracy, efficiency, and data integration. Despite challenges like data quality and ethical concerns, AI’s potential in genomics continues to grow, shaping the future of healthcare.

Neural Network 52

Neural Network Deep Learning Machine Learning Artificial Intelligence 52

ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform.

Data Science 52

Data Science NLP Machine Learning Data Analysis 52

Pickl AI

NOVEMBER 28, 2024

Together, cloud computing and big data tools enable ML engineers to build powerful, scalable models that can handle the demands of modern Data Science. Applying best practices in version control, testing, and code optimisation can dramatically improve the quality and scalability of ML systems.

Machine Learning 52

Machine Learning Neural Network ML Engineer Algorithm 52

ODSC - Open Data Science

SEPTEMBER 17, 2024

This talk will cover the critical challenges faced and steps needed when transitioning from a demo to a production-quality RAG system for professional users of academic data, such as researchers, students, librarians, research officers, and others.

LLM 52

LLM Large Language Models Metadata Data Science 52

The MLOps Blog

AUGUST 3, 2023

Stefan is a software engineer, data scientist, and has been doing work as an ML engineer. He also ran the data platform in his previous company and is also co-creator of open-source framework, Hamilton. We thought, “how can we lower the software engineering bar?”

ML 52

ML Data Scientist Software Engineer Machine Learning 52

ODSC - Open Data Science

SEPTEMBER 13, 2024

You need to plan and design it well to make sure the graph shows the data and how things are connected right. Data Quality The effectiveness of GraphRAG depends on the quality of the data used to create the graph.

Data Science 40

Data Science Artificial Intelligence Artificial Intelligence Natural Language Processing 40

Pickl AI

AUGUST 1, 2024

Collaboratio n: Working with data scientists, software engineers, and other stakeholders to integrate Deep Learning solutions into existing systems. Data Quality and Quantity Deep Learning models require large amounts of high-quality, labelled training data to learn effectively.

Deep Learning 52

Deep Learning Neural Network Machine Learning Natural Language Processing 52

Mlearning.ai

FEBRUARY 15, 2024

Automation eliminates potential mistakes and enhances the data quality of the system. With the help of a reliable software engineering partner , you can streamline your journey toward automation mastery and celebrate incredible results for your business. Originally published at [link] on October 5, 2022. ?

Robotics 52

Robotics Automation Software Engineer Software Development 52

Sebastian Ruder

JANUARY 24, 2022

  Being able to automatically synthesize complex programs is useful for a wide variety of applications such as supporting software engineers.   It is still an open question how much code generation models improve the workflow of software engineers in practice [85]. What’s next?  

NLP 52

NLP ML BERT Computational Linguistics 52

The MLOps Blog

JULY 18, 2023

You have a bit of education in music composition, math, and science before you get more into the software engineering side of things. But you have started out in software design engineering, is that correct? How do you ensure data quality when building NLP products? Data quality is critical.

Conversational AI 52

Conversational AI Natural Language Processing Machine Learning AI 52

The MLOps Blog

MAY 9, 2023

The components comprise implementations of the manual workflow process you engage in for automatable steps, including: Data ingestion (extraction and versioning). Data validation (writing tests to check for data quality). Data preprocessing. Model performance analysis and evaluation.

ML 98

ML Machine Learning Metadata Data Science 98

Unite.AI

MARCH 13, 2024

By using a soft prompt as an initial prefix, followed by task-specific human-engineered prompts and examples, Med-PaLM achieved impressive results on benchmarks like MultiMedQA, which includes datasets such as LiveQA TREC 2017, MedicationQA, PubMedQA, MMLU, MedMCQA, USMLE, and HealthSearchQA.

Natural Language Processing 204

Natural Language Processing Large Language Models Data Scarcity LLM 204

AWS Machine Learning Blog

SEPTEMBER 9, 2024

Generative artificial intelligence (AI) has revolutionized this by allowing users to interact with data through natural language queries, providing instant insights and visualizations without needing technical expertise. This can democratize data access and speed up analysis.

Software Architect 117

Software Architect Generative AI AI AI 117