Flipboard

JANUARY 10, 2025

Quantitative evaluation shows superior performance of biophysical motivated synthetic training data, even outperforming manual annotation and pretrained models. This underscores the potential of incorporating biophysical modeling for enhancing synthetic training data quality.

Deep Learning 86

Deep Learning Deep Learning Artificial Intelligence Artificial Intelligence 86

AWS Machine Learning Blog

JULY 8, 2024

The Data Quality Check part of the pipeline creates baseline statistics for the monitoring task in the inference pipeline. Within this pipeline, SageMaker on-demand Data Quality Monitor steps are incorporated to detect any drift when compared to the input data.

AWS 123

AWS ML ML Data Scientist 123

Pickl AI

DECEMBER 25, 2024

Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Techniques such as data cleansing, aggregation, and trend analysis play a critical role in ensuring data quality and relevance. In contrast, Data Science demands a stronger technical foundation.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Towards AI

FEBRUARY 13, 2024

Thinking about High-Quality Human Data High-quality, detailed human annotations are crucial for creating effective deep learning models, ensuring AI accuracy through tasks such as content classification and language model alignment. This article shared the practices and techniques for improving data quality.

AI 105

AI AI Computer Science Computer Science 105

AWS Machine Learning Blog

NOVEMBER 1, 2024

Our experiments demonstrate that careful attention to data quality, hyperparameter optimization, and best practices in the fine-tuning process can yield substantial gains over base models. Fang Liu holds a master’s degree in computer science from Tsinghua University.

Data Preparation 99

Data Preparation Machine Learning Machine Learning ML 99

Pickl AI

APRIL 21, 2025

Real-World Example: Healthcare systems manage a huge variety of data: structured patient demographics, semi-structured lab reports, and unstructured doctor’s notes, medical images (X-rays, MRIs), and even data from wearable health monitors. Ensuring data quality and accuracy is a major challenge.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

Dataconomy

JULY 25, 2023

Data science can be understood as a multidisciplinary approach to extracting knowledge and actionable insights from structured and unstructured data. It combines techniques from mathematics, statistics, computer science, and domain expertise to analyze data, draw conclusions, and forecast future trends.

Data Science 91

Data Science Data Scientist Machine Learning Machine Learning 91

Dataconomy

SEPTEMBER 27, 2024

Could you share the key milestones that have shaped your career in data analytics? My journey began at NUST MISiS, where I studied Computer Science and Engineering. I studied hard and was a very active student, which made me eligible for an exchange program at Häme University of Applied Sciences (HAMK) in Finland.

Analytics 113

Analytics Analytics Big Data Big Data 113

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. Data Quality and Governance Ensuring data quality is a critical aspect of a Data Engineer’s role.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

AWS Machine Learning Blog

SEPTEMBER 8, 2023

The following figure shows the model improvement for the AutoGluon using different data processing techniques over the period of this engagement. The key observation is as we improve the data quality and quantity the performance of the model in terms of recall improved from below 30% to 78%. Having received his B.S.

Machine Learning 125

Machine Learning Machine Learning AWS ML 125

Women in Big Data

DECEMBER 13, 2023

Dr Sonal Khosla (Speaker) holds a PhD in Computer Science with a specialization in Natural Language Processing from Symbiosis International University, India with publications in peer reviewed Indexed journals. Computational Linguistics is rule based modeling of natural languages. With issues also come the challenges.

Natural Language Processing 52

Natural Language Processing Big Data Big Data Computer Science 52

Pickl AI

MARCH 3, 2025

Business Requirements Analysis and Translation Working with business users to understand their data needs and translate them into technical specifications. Data Quality Assurance Implementing data quality checks and processes to ensure data accuracy and reliability.

Business Intelligence 52

Business Intelligence Business Intelligence Data Analyst Data Visualization 52

Pickl AI

MAY 30, 2024

Understanding Data Science Data Science involves analysing and interpreting complex data sets to uncover valuable insights that can inform decision-making and solve real-world problems. This crucial stage involves data cleaning, normalisation, transformation, and integration.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Pickl AI

DECEMBER 4, 2023

Data governance and security Like a fortress protecting its treasures, data governance, and security form the stronghold of practical Data Intelligence. Think of data governance as the rules and regulations governing the kingdom of information. It ensures data quality , integrity, and compliance.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

Dataconomy

MARCH 24, 2023

BI developer:  A BI developer is responsible for designing and implementing BI solutions, including data warehouses, ETL processes, and reports. They may also be involved in data integration and data quality assurance. To pursue a career path in BI, a strong background in data analysis and programming is essential.

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Dataconomy

MARCH 24, 2023

BI developer:  A BI developer is responsible for designing and implementing BI solutions, including data warehouses, ETL processes, and reports. They may also be involved in data integration and data quality assurance. To pursue a career path in BI, a strong background in data analysis and programming is essential.

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Snorkel AI

JANUARY 26, 2024

Snorkel engineers and researchers, he noted, used scalable data development tools to improve many parts of this system, including their embedding and retrieval models. LLMs require three sequential stages of training, he noted, and harmonizing training data across these stages is crucial for their effectiveness.

Data Science 64

Data Science AI AI Machine Learning 64

Pickl AI

JULY 12, 2024

Natural Language Processing (NLP) This is a field of computer science that deals with the interaction between computers and human language. Computer Vision This is a field of computer science that deals with the extraction of information from images and videos.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

AWS Machine Learning Blog

JULY 10, 2024

Generally, as the size of the high-quality training data increases, you can expect to achieve better performance from the fine-tuned model. However, it’s essential to maintain a focus on data quality, because a large but low-quality dataset may not yield the desired improvements in the fine-tuned model performance.

AWS 132

AWS AI AI ML 132

AWS Machine Learning Blog

FEBRUARY 28, 2023

If you want to add rules to monitor your data pipeline’s quality over time, you can add a step for AWS Glue Data Quality. And if you want to add more bespoke integrations, Step Functions lets you scale out to handle as much data or as little data as you need in parallel and only pay for what you use.

ML 101

ML ML AWS Machine Learning 101

Heartbeat

OCTOBER 25, 2023

Empowering Data Scientists and Machine Learning Engineers in Advancing Biological Research Image from European Bioinformatics Institute Introduction: In biological research, the fusion of biology, computer science, and statistics has given birth to an exciting field called bioinformatics.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Algorithm 52

Dataconomy

MARCH 13, 2023

How to create an artificial intelligence: Building accurate and efficient AI systems requires selecting the right algorithms and models that can perform the desired tasks effectively Developing AI Developing AI involves a series of steps that require expertise in several fields, such as data science, computer science, and engineering.

Artificial Intelligence 98

Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

Pickl AI

DECEMBER 3, 2024

Connection to the University of California, Irvine (UCI) The UCI Machine Learning Repository was created and is maintained by the Department of Information and Computer Sciences at the University of California, Irvine.

Machine Learning 52

Machine Learning Machine Learning Clustering Supervised Learning 52

Snorkel AI

JANUARY 26, 2024

Snorkel engineers and researchers, he noted, used scalable data development tools to improve many parts of this system, including their embedding and retrieval models. LLMs require three sequential stages of training, he noted, and harmonizing training data across these stages is crucial for their effectiveness.

Data Science 52

Data Science Data Scientist AI AI 52

Heartbeat

AUGUST 23, 2023

NLP is fundamentally an interdisciplinary field that blends linguistics, computer science, and artificial intelligence to provide robots with the capacity to comprehend and analyze human language. Data Quality and Bias NLP systems rely significantly on massive training data to understand patterns and generate accurate predictions.

Natural Language Processing 52

Natural Language Processing Algorithm Artificial Intelligence Artificial Intelligence 52

Pickl AI

AUGUST 1, 2024

Data Quality and Quantity Deep Learning models require large amounts of high-quality, labelled training data to learn effectively. Insufficient or low-quality data can lead to poor model performance and overfitting. TensorFlow, PyTorch), and knowledge of neural network architectures are also crucial.

Deep Learning 52

Deep Learning Deep Learning Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 3, 2023

It is a branch of computer science that focuses on developing machines capable of mimicking human intelligence. It went from simple rule-based systems to advanced data-driven algorithms. Click here to know more about how one can unleash the power of AI and ML for scaling operations and data quality.

AI 52

AI AI Artificial Intelligence Artificial Intelligence 52

ODSC - Open Data Science

APRIL 26, 2023

This is a position that requires a mathematical and analytical methodology to assist organizations to solve complex problems and make data-driven decisions in dynamic environments. Due to the nature of the job, these analysts require a strong background in mathematics, computer science, and statistics to get the job done.

Data Analyst 52

Data Analyst Machine Learning Machine Learning Power BI 52

Snorkel AI

APRIL 28, 2023

Ce Zhang is an associate professor in Computer Science at ETH Zürich. He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. You could have a missing value, you could have a wrong value, and you have a whole bunch of those data examples.

ML 52

ML ML Machine Learning Machine Learning 52

Snorkel AI

APRIL 28, 2023

Ce Zhang is an associate professor in Computer Science at ETH Zürich. He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. You could have a missing value, you could have a wrong value, and you have a whole bunch of those data examples.

ML 52

ML ML Machine Learning Machine Learning 52

Snorkel AI

OCTOBER 12, 2023

Applying Weak Supervision and Foundation Models for Computer Vision In this session, Snorkel’s own ML Research Scientist Ravi Teja Mullapudi explores the latest advancements in computer vision that enable data-centric image classification model development. image-text pairs from Common Crawl.

AI 64

AI AI ML ML 64

Snorkel AI

OCTOBER 12, 2023

Applying Weak Supervision and Foundation Models for Computer Vision In this session, Snorkel’s own ML Research Scientist Ravi Teja Mullapudi explores the latest advancements in computer vision that enable data-centric image classification model development. image-text pairs from Common Crawl.

AI 59

AI AI ML ML 59

Chatbots Life

SEPTEMBER 11, 2023

Natural Language Processing (NLP) is an interdisciplinary field that combines the expertise of linguistics, computer science, and artificial intelligence to enable computers to process and comprehend human language. Grammar Checker Limitation of grammar checker as follows.

Natural Language Processing 59

Natural Language Processing Python ML ML 59

Pickl AI

SEPTEMBER 12, 2024

Key Components of Data Science Data Science consists of several key components that work together to extract meaningful insights from data: Data Collection: This involves gathering relevant data from various sources, such as databases, APIs, and web scraping.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Snorkel AI

OCTOBER 12, 2023

Applying Weak Supervision and Foundation Models for Computer Vision In this session, Snorkel’s own ML Research Scientist Ravi Teja Mullapudi explores the latest advancements in computer vision that enable data-centric image classification model development. image-text pairs from Common Crawl.

AI 52

AI AI ML ML 52

Dataconomy

MAY 3, 2023

Artificial intelligence (AI) is a subfield of computer science that tries to program computers to mimic human intellect in areas like learning, thinking, and decision-making. They may face technical limitations, such as data quality, scalability, image generation, and security.

AI 202

AI AI Artificial Intelligence Artificial Intelligence 202

Flipboard

JULY 31, 2023

The training set acts as a crucible for model training, the validation set assists in gauging the model’s performance, and the test set allows for performance appraisal on unfamiliar data. Three synchronized and calibrated Kinect V2 cameras captured the dataset, ensuring consistent data quality. That’s not the case.

Machine Learning 123

Machine Learning Machine Learning Deep Learning Deep Learning 123