Delve into the world of skin boosters and skin health through this comprehensive online training session. Explore topics such as Vision Blend New Day, Skin Improvement and Supplements, Skin Booster application, and more. Understand the causes of skin issues like acne, rosacea, and imbalanced skin, a

3 views • 19 slides

Real-world Evidence (RWE) Solutions Market by Component (Datasets [Clinical, Claims, Pharmacy, Integrated], Services), Application (Market Access, Oncology, Neurology, Post Market Surveillance), End User (Pharma Companies, Providers) - Global Forecast to 2029

2 views • 3 slides

Large Language Models (LLMs) are sophisticated deep learning algorithms capable of understanding and generating human language. These models, trained on massive datasets, excel at various natural language processing tasks such as sentiment analysis, text classification, natural language inference, s

2 views • 83 slides

This course at National Taipei University delves into fundamental concepts, research issues, and practical applications of Big Data Analysis. Taught by Dr. Min-Yuh Day, the syllabus covers topics such as AI, machine learning, deep learning, and industry practices related to big data analysis. Studen

5 views • 80 slides

Addressing the challenge of imbalanced datasets in machine learning is crucial, as standard classifiers tend to favor majority classes, leading to poor performance on minority classes. This imbalance can impact various domains, such as fraud detection and cancer diagnosis. Strategies like data balan

2 views • 54 slides

The VNA & PACS Market is projected to reach $6.50 billion by 2031, at a CAGR of 7.2% from 2024 to 2031. Vendor Neutral Archive (VNA) & Picture Archiving and Communication System (PACS) are medical image management solutions used for aiding diagnosis, comparing images between patients or within the s

1 views • 4 slides

The AnglE model introduces angle optimization to address common challenges like vanishing gradients and underutilization of supervised negatives in Large Language Models (LLMs). By enhancing the gradient and optimization processes, this novel approach improves text embedding learning effectiveness.

9 views • 33 slides

Spatial data mining involves uncovering valuable patterns from extensive spatial datasets, offering insights into historical events, environmental phenomena, and predictive analytics. Examples range from analyzing disease outbreaks to predicting habitat suitability for endangered species. The applic

1 views • 20 slides

Explore the world of biological datasets, lipidomics, genomics, epigenomics, proteomics, and the application of omics in studying biological mechanisms, predicting outcomes, and identifying important variables. Dive into DNA, gene expression, methylation, and genetic datasets to unravel the complexi

0 views • 34 slides

VSAM utilizes three primary methods to find logical records - Relative Byte Address, Relative Record Number, and Key field. Relative Byte Address assigns a unique address to each record based on sequential ordering. Relative Record Number is used in RRDS datasets to access records by a numbered sequ

1 views • 35 slides

Explore the latest primary tumour staging changes for skin cancer, including updates from RCPath, datasets for BCC and SCC, changes in TNM classification for skin carcinomas, and upcoming new college datasets. Dive into the evolving landscape of skin cancer staging since January 2018 with detailed s

0 views • 11 slides

This content provides a detailed walkthrough of utilizing Perseus interface/functions for analyzing label-free and SILAC datasets in the field of proteomics. It covers loading, filtering, visualization, log transformation, rearrangement of columns, and advanced analysis techniques such as scatter pl

2 views • 4 slides

Understanding simulation studies and their importance in evaluating statistical methods, this presentation delves into the precise coding techniques required in Stata to generate simulated datasets, produce estimates, and analyze performance metrics. With a focus on consistent terminology, data-gene

5 views • 18 slides

Project EDDIE focuses on improving student quantitative reasoning through inquiry-driven exploration of complex datasets. The project aims to support instructors in guiding students to enhance their understanding of scientific concepts and quantitative skills. With a commitment to community and lear

0 views • 6 slides

Investigating natural language interfaces for querying structured MOF data stored in a knowledge graph, this project focuses on developing strategies using NLP to translate NL questions to KG queries. The MOF-KG integrates datasets, enabling query, computation, and reasoning for deriving new knowled

0 views • 13 slides

Discover a plethora of sources, tools, and datasets in text mining through resources shared by Bettina Berendt and references from lectures and publications. Uncover DH-specific tools and powerful NLP tools like Ling Pipe, OpenNLP, Stanford Parser, and NLTK Toolkit for text analysis and processing.

0 views • 17 slides

Dive into the world of data analysis using RCommander with this comprehensive guide. Learn how to import, clean, and analyze data efficiently, ensuring your datasets are well-prepared for insightful insights. Follow simple steps to navigate RCommander, import Excel files, save datasets, and review v

0 views • 17 slides

A comprehensive guide providing side-by-side code examples in Stata, Python, and R, facilitating easy translation between the languages. It covers setting up Python for Stata, handling dataframes, storing datasets, working with log files, merging datasets, describing and summarizing data, and more.

0 views • 21 slides

Addressing the challenges posed by imbalanced class problems in data mining is crucial for accurate classification. Class imbalance can affect evaluation measures like accuracy and requires alternative techniques such as precision, recall, and F-measure. Detecting rare classes, such as credit card f

0 views • 30 slides

Collective qualitative secondary analysis involves reusing data through a collaborative lens, embracing multiple viewpoints to gain deeper insights. The approach emphasizes the constructed nature of research data and allows for diverse interpretations and engagements. This article discusses the proc

0 views • 15 slides

The SAMME.C2 algorithm addresses severely imbalanced multi-class classification problems by utilizing boosting techniques such as AdaBoost and cost-sensitive learning. Through numerical experiments and performance statistics, the algorithm shows the trade-off between accurately classifying minority

0 views • 5 slides

Dawn Archer and Bethan Malory explore the tracing of verbal aggression and other facework strategies over time using themes from the Historical Thesaurus of English. They utilize automated content analysis tools to analyze datasets from various historical periods and propose solutions for prioritizi

0 views • 41 slides

Large, dynamic data user and enterprise-generated data are increasingly popular, leading to the need for better data management systems. Today's approaches involve handling evolving datasets, algorithmic trading, log analysis, and more. The DBToaster project focuses on lightweight systems for managi

0 views • 37 slides

Explore the integration of relational databases with QGIS to facilitate efficient spatial data analysis. Discover the importance of recognizing spatial relationships within data sets and the solutions to enhance QGIS for relational datasets. Overcome challenges and delve into the intersection and su

0 views • 25 slides

Americans are advised to increase their intake of vegetables, fruits, whole grains, low-fat dairy, seafood, and healthy oils. It's important to understand caloric needs based on age, activity level, and gender. The new 9th-grade rule sets calorie limits for school meals. Relying on all three factors

0 views • 16 slides

Proper dataset handling is crucial in machine learning projects. Use publicly available datasets with train/dev/test splits or create your own. Be cautious of overfitting by utilizing independent validation and test sets. Avoid touching the test set until final evaluation to prevent overfitting. Mai

0 views • 13 slides

The VIIRS Land Surface Temperature (LST) Provisional Status project, led by Dr. Yunyue Yu, focuses on improving the LST EDR through algorithm coefficient updates and calibrations. The calibration process involves regression steps and comparisons with reference datasets like MODIS Aqua LST. Various c

0 views • 29 slides

AFNI_proc.py is a Python program that provides a flexible and compact way to process and analyze datasets in AFNI. It takes input options to describe processing steps, producing a Unix script file that runs AFNI programs for data analysis. The script not only performs data analysis but also saves di

0 views • 37 slides

An introductory course designed for researchers familiar with basic statistics but new to using international education datasets such as PISA and TALIS. The course includes lectures, practical activities, and computer workshops covering survey design, cross-national comparisons, and data analysis. P

0 views • 53 slides

Archives existing within libraries bring about both collaboration opportunities and challenges due to imbalanced power dynamics. Research explores corporate identity, relationships, and user experiences in such setups. Methodology includes case studies, interviews, and surveys. Insights reveal colla

0 views • 11 slides

The UCR Time Series Classification Archive, funded by NSF IIS-1161997 II and NSF IIS-1510741, provides valuable resources for researchers interested in time series data analysis. The archive contains datasets in TRAIN and TEST partitions, with data instances stored in ASCII format. Researchers can u

0 views • 14 slides

This detailed summary provides information on significant brain-related project datasets and consortia, including PsychENCODE, BrainSpan, CommonMind Consortium, AMP-AD Knowledge, and more. Each dataset or consortium focuses on specific areas such as genomics, neuropsychiatric diseases, neurodegenera

0 views • 18 slides

The National Maternity and Perinatal Audit (NMPA) collects data extracts from various datasets in England, Wales, and Scotland to improve maternity and perinatal services. The datasets include mortality registers, birth notification datasets, maternity services data sets, and more. The collected dat

0 views • 5 slides

The workshop held in Tunisia aimed to improve national food composition datasets, focusing on countries in the Eastern Mediterranean Region and Africa. Key objectives included identifying existing data status, providing training on data compilation, and generating harmonized datasets for EuroFIR. Th

0 views • 15 slides

Learn how to install Apache Singa, prepare data using SINGA recognizable records, and convert programs for DataShard for efficient handling of CIFAR-10 and MNIST datasets. Explore examples on creating shards, generating records, and implementing CNN layers for effective deep learning.

0 views • 23 slides

This study focuses on optimizing train unit scheduling by satisfying capacity requirements and minimizing operating costs. The research addresses imbalanced demands and under-utilized train units, proposing solutions for re-balancing. It explores integer multicommodity flow representation and method

0 views • 33 slides

This study delves into allelic bias in personal genomes, examining the influence of various factors such as sequencing datasets, removal of reads with allelic bias, and the impact on allele-specific single nucleotide variants (AS SNVs). The revised AlleleDB pipeline proposed includes steps for const

0 views • 6 slides

The National Maternity and Perinatal Audit (NMPA) in England, Wales, and Scotland receives various datasets for maternal and perinatal care, including mortality data, birth notifications, maternity services data, and more. The datasets are pseudonymised and used for linkage, validation, case ascerta

0 views • 5 slides

National data catalogues have specific requirements for identifiers, such as using HTTP URIs for open data datasets. While most INSPIRE datasets only have UUID identifiers, adhering to the DCAT-AP standard recommends using HTTP URIs. Recommendations for creating identifiers in the geodata sector are

0 views • 5 slides

Explore the challenges of imbalanced data in machine learning, illustrated through a scenario involving phishing email classification. Learn why classifiers tend to predict the majority class, strategies to address imbalance, and common domains with imbalanced data issues such as medical diagnosis a

0 views • 50 slides