Marktechpost

NOVEMBER 11, 2024

Python has become the go-to language for data analysis due to its elegant syntax, rich ecosystem, and abundance of powerful libraries. Data scientists and analysts leverage Python to perform tasks ranging from data wrangling to machine learning and data visualization.

Data Analysis 92

Data Analysis Python Natural Language Processing Computer Vision 92

Unite.AI

DECEMBER 5, 2024

As they constantly upgrade and develop, AI systems improve their predictive abilities and data analysis, allowing providers to update their services and ensure customer satisfaction. In addition, AI efficiently categorizes threats by assessing their potential severity, impact and damage.

Data Analysis 173

Data Analysis Automation AI AI 173

SAS Software

JANUARY 8, 2024

The post Reporting statistics for unobserved levels of categorical variables appeared first on SAS Blogs. For example, in a small sample of US voters, you are likely to observe members of the major political parties, but less likely to observe members of minor or fringe parties. This can cause a headache [.]

Categorization 72

Categorization Data Analysis 72

AssemblyAI

MAY 24, 2024

4 Ways to Use Speech AI for Healthcare Market Research Speech AI helps researchers gain deeper insights, improve the accuracy of their data, and accelerate the time from research to actionable results. Marvin is a qualitative data analysis platform that has integrated advanced AI models to accelerate and improve its research processes.

Categorization 147

Categorization Data Analysis AI AI 147

Unite.AI

NOVEMBER 22, 2024

This new breed of product professionals will be able to meld their strategic expertise with deep knowledge of design, coding, and data analysis by applying AI to amplify their capabilities. This affects everything from ideation and execution to alignment with stakeholders and leading with influence.

Data Analysis 147

Data Analysis AI AI Artificial Intelligence 147

Mlearning.ai

FEBRUARY 28, 2023

Theoretical Explanations and Practical Examples of Correlation between Categorical and Continuous Values Without any doubt, after obtaining the dataset, giving entire data to any ML model without any data analysis methods such as missing data analysis, outlier analysis, and correlation analysis.

Categorization 52

Categorization Data Analysis Neural Network ML 52

Pickl AI

JUNE 11, 2024

Summary: Exploratory Data Analysis (EDA) uses visualizations to uncover patterns and trends in your data. Histograms, scatter plots, and charts reveal relationships and outliers, helping you understand your data and make informed decisions. Imagine a vast, uncharted territory – your data set.

Data Analysis 52

Data Analysis Categorization Data Discovery Data Science 52

Marktechpost

AUGUST 23, 2024

This challenge becomes even more complex given the need for high predictive accuracy and robustness, especially in critical applications such as health care, where the decisions among data analysis can be quite consequential. Different methods have been applied to overcome these challenges of modeling tabular data.

Data Analysis 69

Data Analysis Categorization Large Language Models Machine Learning 69

Heartbeat

JANUARY 24, 2024

Making visualizations is one of the finest ways for data scientists to explain data analysis to people outside the business. Exploratory data analysis can help you comprehend your data better, which can aid in future data preprocessing. Exploratory Data Analysis What is EDA?

Data Analysis 52

Data Analysis Categorization Data Scientist Machine Learning 52

Towards AI

FEBRUARY 26, 2024

Data Collection Exploration and Analysis Data Collection Visualization of data and summary of observations 3. Data Pre-Processing Handling Missing Values Encoding Categorical Variables Feature Scaling Data Splitting (Training and Validation) 4. abdomo protein’: Protein level in the abdominal fluid.

Machine Learning 115

Machine Learning Categorization Data Analysis Python 115

IBM Journey to AI blog

DECEMBER 20, 2023

Classification algorithms —predict categorical output variables (e.g., “junk” or “not junk”) by labeling pieces of input data. Regression algorithms —predict output values by identifying linear relationships between real or continuous values (e.g., temperature, salary).

Machine Learning 230

Machine Learning Neural Network Algorithm Computer Vision 230

Pickl AI

OCTOBER 14, 2024

Summary: This article explores different types of Data Analysis, including descriptive, exploratory, inferential, predictive, diagnostic, and prescriptive analysis. Introduction Data Analysis transforms raw data into valuable insights that drive informed decisions. What is Data Analysis?

Data Analysis 52

Data Analysis Data Mining Data Discovery Machine Learning 52

Pickl AI

MAY 30, 2024

Summary: The Data Science and Data Analysis life cycles are systematic processes crucial for uncovering insights from raw data. Quality data is foundational for accurate analysis, ensuring businesses stay competitive in the digital landscape. billion INR by 2026, with a CAGR of 27.7%.

Data Analysis 52

Data Analysis Data Science Data Scientist Data Quality 52

Marktechpost

SEPTEMBER 26, 2023

In the domain of reasoning under uncertainty, probabilistic graphical models (PGMs) have long been a prominent tool for data analysis. Many graphical models are designed to work exclusively with continuous or categorical variables, limiting their applicability to data that spans different types.

Neural Network 136

Neural Network Categorization Data Scientist Data Analysis 136

Unite.AI

SEPTEMBER 18, 2023

Blockchain technology can be categorized primarily on the basis of the level of accessibility and control they offer, with Public, Private, and Federated being the three main types of blockchain technologies. Large-scale data analysis methods that offer privacy protection by utilizing both blockchain and AI technology.

Deep Learning 321

Deep Learning Artificial Intelligence Artificial Intelligence AI 321

SAS Software

JULY 17, 2023

The post Standardize regression coefficients for models that include categorical variables appeared first on SAS Blogs. It also discusses how to interpret a standardized regression coefficient. Recently, a SAS user wanted to know how [.]

Categorization 52

Categorization Data Analysis 52

Towards AI

APRIL 7, 2024

Figure 3: The required python libraries The problem presented to us is a predictive analysis problem which means that we will be heavily involved in finding patterns and predictions rather than seeking recommendations. One important stage of any data analysis/science project is EDA. Exploratory Data Analysis is a pre-study.

Machine Learning 124

Machine Learning Data Analysis Data Science Automation 124

AWS Machine Learning Blog

JUNE 25, 2024

Manually analyzing and categorizing large volumes of unstructured data, such as reviews, comments, and emails, is a time-consuming process prone to inconsistencies and subjectivity. We provide a prompt example for feedback categorization. For more information, refer to Prompt engineering. No explanation is required.

Automation 132

Automation Prompt Engineer Prompt Engineering Categorization 132

AssemblyAI

MARCH 3, 2024

This article examines how AI models can be leveraged to help market research platforms build powerful tools that can: Transcribe asynchronous and live voice and video feedback to make review and analysis more efficient. Generate key themes and highlights to speed up research analysis.

Categorization 147

Categorization Large Language Models AI AI 147

Marktechpost

MAY 18, 2024

Effective graph pooling is essential for downsizing and learning representations, categorized into global and hierarchical pooling. GNNs, classified into spectral-based and spatial-based, excel in graph data analysis. Both face over-smoothing issues, addressed by models like MixHop and N-GCN.

Neural Network 111

Neural Network Categorization Deep Learning Data Analysis 111

Marktechpost

MAY 7, 2024

Moreover, differences in data table structures between BI and traditional SQL contexts further complicate the translation process. As thousands of organizations leverage Business Intelligence (BI) for decision support, industry researchers have honed in on NL2BI, a scenario where natural language is transformed into BI queries.

Business Intelligence 119

Business Intelligence Prompt Engineer Prompt Engineering Natural Language Processing 119

Marktechpost

DECEMBER 25, 2023

This feature helps uncover patterns within the data, making it much easier to identify trends and relationships. Imagine organizing and categorizing information in a way that reveals valuable insights without manually sifting through endless data points.

Natural Language Processing 115

Natural Language Processing Categorization Data Analysis NLP 115

Mlearning.ai

APRIL 17, 2023

Without further ado, let’s dive in to our study… Photograph Via : Steven Yu | Pexels, Pixabay Hello, my previous work Analyzing and Visualizing Earthquake Data Received with USGS API in Python Environment I prepared a new work after 3 weeks. Now, I will be conducting an exploratory data analysis study. value_counts().to_dict()

Data Analysis 52

Data Analysis Categorization Explainability ML 52

AssemblyAI

MAY 14, 2024

Automated Data Analysis Marvin integrates advanced AI models to provide automated transcription services that convert audio and video data into accurate, actionable text. It lets users analyze text to detect patterns, extract meaningful information, and even redact sensitive data (automatically). For example, Corti.ai

Natural Language Processing 147

Natural Language Processing Automation Robotics Categorization 147

AssemblyAI

NOVEMBER 30, 2023

  Source: CallRail For example, its AI Conversational Intelligence feature auto-scores and categorizes key sections of customers’ calls, helping users more efficiently and intelligently process call data at scale.

Large Language Models 147

Large Language Models Data Analysis AI Tools AI 147

Marktechpost

JULY 18, 2024

This approach involves generalizing classical statistical and deep learning methods to handle data that does not conform to traditional Euclidean assumptions. The researchers have developed a graphical taxonomy that categorizes these modern techniques, facilitating an understanding of their applications and relationships.

Machine Learning 135

Machine Learning Computer Vision Neural Network Deep Learning 135

IBM Journey to AI blog

AUGUST 28, 2023

Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data. It also automates tasks like information extraction and content categorization. positive, negative or neutral).

Data Mining 170

Data Mining Convolutional Neural Networks Categorization Machine Learning 170

Marktechpost

SEPTEMBER 8, 2023

Microsoft Power BI Microsoft Power BI, a powerful business intelligence platform that lets users filter through data and visualize it for insights, is another top AI tool for data analysis. Users may import data from practically anywhere into the platform and immediately create reports and dashboards.

AI Tools 133

AI Tools Data Science Machine Learning Data Analysis 133

Marktechpost

MARCH 21, 2024

Previous strategies have primarily focused on improving the models’ ability to recognize and categorize visual elements. Yet, the leap from mere recognition to sophisticated reasoning, where a model sees, understands, and infers from visual data, has to be discovered.

AI Researcher 133

AI Researcher AI Research Large Language Models Categorization 133

Unite.AI

AUGUST 27, 2024

It allows you to save, annotate, and categorize resources, turning Perplexity into a personal knowledge base. Collections in Perplexity allowed me to categorize my Threads for better management and easy access. It's worth paying for Perplexity if you need more robust tools for advanced research and data analysis.

ChatGPT 264

ChatGPT AI AI AI Tools 264

ODSC - Open Data Science

FEBRUARY 6, 2023

Advanced Gradient Boosting: Probabilistic Regression and Categorical Structure Brian Lucena | Principal | Numeristical Join this hands-on training to learn some of the more advanced, cutting-edge techniques for gradient boosting.

Categorization 98

Categorization Data Science Data Scientist Deep Learning 98

Towards AI

NOVEMBER 8, 2023

As shown in the profile of the dataset, there are both integer and categorical features. There’re some interesting details in the data. In order for the model to learn about personalized interactions, both the user and the product features must be treated as categorical features. All three are labelled with numbers.

Categorization 124

Categorization Explainability Machine Learning Data Analysis 124

Pickl AI

AUGUST 1, 2023

Moreover, using sentiment analysis techniques, organizations can gain valuable insights into customer satisfaction, identify trends, and make data-driven improvements. Topic Modeling With text mining, it is possible to identify and categorize topics and themes within large collections of documents.

Data Analysis 52

Data Analysis Python Categorization Data Mining 52

AssemblyAI

JANUARY 23, 2024

Its AI Conversational Intelligence feature also helps its customers more efficiently process call data at scale by auto-scoring and categorizing key sections of customer calls.  More personalized analysis tools Product teams can also integrate LLMs to offer more personalized analysis tools for end users. 

Large Language Models 147

Large Language Models Natural Language Processing Categorization Automation 147

Marktechpost

DECEMBER 24, 2023

Specifically in plant pathology, its rapid data analysis revolutionizes disease management, offering efficient solutions for crop protection and heightened productivity. Agriculture stands as the bedrock of humanity’s sustenance. In this critical realm, the transformative power of machine learning is reshaping the landscape.

Machine Learning 121

Machine Learning Convolutional Neural Networks Neural Network Deep Learning 121

Towards AI

APRIL 7, 2024

Data Collection and Preprocessing The first step in building any machine learning model is to gather and preprocess your data. This often involves dealing with missing values, handling categorical variables, and scaling numerical features. This involves visualizing the data and analyzing key statistics.

AI Modeling 105

AI Modeling Machine Learning Categorization Data Analysis 105

Marktechpost

NOVEMBER 27, 2024

Types of Machine Learning: Supervised Learning: Involves training a model on labeled data. Classification: Categorizing data into discrete classes (e.g., Unsupervised Learning: Involves training a model on unlabeled data. Clustering: Grouping similar data points together (e.g., spam filtering, sentiment analysis).

Machine Learning 116

Machine Learning Algorithm Neural Network Convolutional Neural Networks 116