Viso.ai

APRIL 25, 2024

Bias detection in Computer Vision (CV) aims to find and eliminate unfair biases that can lead to inaccurate or discriminatory outputs from computer vision systems. Computer vision has achieved remarkable results, especially in recent years, outperforming humans in most tasks. Let’s get started.

Computer Vision 52

Computer Vision Categorization Algorithm Machine Learning 52

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

Viso.ai

DECEMBER 19, 2023

This article covers everything you need to know about image classification – the computer vision task of identifying what an image represents. provides the end-to-end Computer Vision Platform Viso Suite. It’s a powerful all-in-one solution for AI vision. How Does Image Classification Work?

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

PyImageSearch

FEBRUARY 6, 2023

If you are a regular PyImageSearch reader and have even basic knowledge of Deep Learning in Computer Vision, then this tutorial should be easy to understand. But we would still apply data augmentation to ensure the model doesn’t overfit and generalize well on the test dataset. Or requires a degree in computer science?

Auto-classification 140

Auto-classification Computer Vision Neural Network Deep Learning 140

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 117

Automation Prompt Engineer Prompt Engineering Categorization 117

Marktechpost

APRIL 29, 2024

Computer vision, machine learning, and data analysis across many fields have all seen a surge in the usage of synthetic data in the past few years. Concerning tabular data, one of the biggest obstacles is maintaining consistency when dealing with fluctuating percentages of numerical and categorical data.

Machine Learning 120

Machine Learning Computer Vision Algorithm Categorization 120

Marktechpost

NOVEMBER 1, 2024

Microsoft Power BI For businesses looking to integrate AI and improve their data analysis capabilities, Microsoft Power BI is a crucial tool. Its advanced text analysis features allow users to extract significant phrases and do sentiment analysis, improving the overall caliber of data insights.

Artificial Intelligence 97

Artificial Intelligence Artificial Intelligence AI Tools Machine Learning 97

Marktechpost

NOVEMBER 4, 2024

Professionals known as data analysts enable this by turning complicated raw data into understandable, useful insights that help in decision-making. They navigate the whole data analysis cycle, from discovering and collecting pertinent data to getting it ready for analysis, interpreting the findings, and formulating suggestions.

Data Analysis 83

Data Analysis Machine Learning Data Science Python 83

Viso.ai

OCTOBER 7, 2024

This is where computer vision technology can help identify waste, separate it, and ensure its proper disposal. In this article, we will propose computer vision as an effective tool for waste management. For truly solving real-world scenarios, organizations require more than just a computer vision tool or algorithm.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Robotics 52

Viso.ai

MARCH 27, 2024

This article explores Kaggle, a popular platform for learning everything related to Data Science, Computer Vision (CV), and Machine Learning. Learning pre-trained models will save a lot of time and resources when working on computer vision tasks. Reproduce already available solutions as well.

Computer Vision 52

Computer Vision Data Scientist Data Science Machine Learning 52

Viso.ai

JANUARY 2, 2024

In the following, we will explore Convolutional Neural Networks (CNNs), a key element in computer vision and image processing. Viso Suite enables the use of neural networks for computer vision with no code. Le propose architectures that balance accuracy and computational efficiency. Learn more and request a demo.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

Pickl AI

JULY 17, 2023

Therefore, it mainly deals with unlabelled data. The ability of unsupervised learning to discover similarities and differences in data makes it ideal for conducting exploratory data analysis. Acquiring unlabelled data from computer systems is easier than labeled data.

Machine Learning 52

Machine Learning Algorithm Categorization Data Analysis 52

Dlabs.ai

DECEMBER 6, 2022

They’re the perfect fit for: Image, video, text, data & lidar annotation Audio transcription Sentiment analysis Content moderation Product categorization Image segmentation iMerit also specializes in extraction and enrichment for Computer Vision , NLP , data labeling, and other technologies.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Computer Vision Machine Learning 52

Chatbots Life

APRIL 16, 2024

Data Augmentation Generative models can generate additional training examples, improving the performance of other machine learning models. By applying generative models in these areas, researchers and practitioners can unlock new possibilities in various domains, including computer vision, natural language processing, and data analysis.

Neural Network 59

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 59

Mlearning.ai

JUNE 2, 2023

Task like building a section of a software or a part of another code can be categorized under Modular Task’s. Computer Vision The golden rule is to balance both. Then there is also Experimental Tasks where the next step is dependent on the previous step and there is no fix flow for the execution of code.

Python 52

Python Neural Network Computer Vision Machine Learning 52

Viso.ai

MAY 21, 2024

At its core, data science is all about discovering useful patterns in data and presenting them to tell a story or make informed decisions. provides a robust end-to-end no-code computer vision solution – Viso Suite. Also, in this phase, we clean the outliers, i.e., data points far from the observed distribution.

Data Science 52

Data Science Python Neural Network Machine Learning 52

Mlearning.ai

JULY 6, 2023

Characteristics of remote sensing data When it comes to working with remote sensing data and deep learning techniques, several things need to be considered since remotely sensed data is quite different from common images in computer vision. Here are some characteristics of remote sensing data: Multiple modalities.

Deep Learning 52

Deep Learning Computer Vision Categorization Big Data 52

Pickl AI

MAY 23, 2023

Kaggle: Kaggle is a popular site for data science competitions. The Kaggle tournaments include an extensive variety of disciplines, including picture categorization, text analysis, and time series forecasting, among others. Data Hack: DataHack is a web-based platform that offers data science competitions and hackathons.

Data Science 52

Data Science Machine Learning Data Mining Algorithm 52

PyImageSearch

JUNE 19, 2023

By the end of the lesson, readers will have a solid grasp of the underlying principles that enable these applications to make suggestions based on data analysis. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Or requires a degree in computer science?

Neural Network 56

Neural Network Computer Vision Data Mining Algorithm 56

Pickl AI

JULY 28, 2023

Numerous industries have undergone a revolution because of their quick improvements, which have also greatly improved automation and visual data analysis capabilities. IR, also known as computer vision, is a field of AR that involves computers’ automatic interpretation and understanding of images.

Machine Learning 52

Machine Learning Convolutional Neural Networks Neural Network Deep Learning 52

PyImageSearch

SEPTEMBER 16, 2024

Anomaly detection ( Figure 2 ) is a critical technique in data analysis used to identify data points, events, or observations that deviate significantly from the norm. Figure 4: Categorization of Anomalies based on type, latency, application, and method (source: ScienceDirect ). Or requires a degree in computer science?

Computer Vision 56

Computer Vision Algorithm Deep Learning Machine Learning 56

Pickl AI

DECEMBER 10, 2024

Categorical Features (Nominal vs. Ordinal) Categorical features group data into distinct categories or classes, often representing qualitative attributes. Handling categorical data appropriately is essential for ensuring accurate interpretations by Machine Learning models.

Machine Learning 52

Machine Learning Convolutional Neural Networks Categorization Automation 52

NVIDIA Developer

MAY 20, 2021

Using deep learning, computers can learn and recognize patterns from data that are considered too complex or subtle for expert-written software. In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing.

Natural Language Processing 40

Natural Language Processing Deep Learning Neural Network NLP 40

Pickl AI

JULY 31, 2023

The primary goal of AI is to create computer systems that can perform tasks that would typically require human intelligence, such as reasoning, problem-solving, learning, understanding natural language, and adapting to new situations. This enables applications such as facial recognition, object detection, and image understanding.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm AI 52

Artificial Corner

JUNE 6, 2023

This made them ideal for trend analysis, business reporting, and decision support. The development of data warehouses marked a shift in how businesses used data, moving from transactional processing to data analysis and decision support. Computer Vision algorithms can be employed for image recognition and analysis.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

DataRobot Blog

DECEMBER 20, 2022

In this educated example , the aim is to predict home prices at the property level in the city of Madrid and the training dataset contains 5 different data types (numerical, categorical, text, location, and images) and +90 variables that are related to these 5 different groups: Market performance. Property performance.

Explainability 59

Explainability Automation Machine Learning AI 59

Mlearning.ai

MAY 23, 2023

The following Venn diagram depicts the difference between data science and data analytics clearly: 3. Data analysis can not be done on a whole volume of data at a time especially when it involves larger datasets. This is where the importance of having proper and clean data comes into the picture.

Data Science 52

Data Science Neural Network Deep Learning Machine Learning 52

Mlearning.ai

JUNE 27, 2023

It is commonly used in computer vision applications, such as object detection, image recognition, and image compression. Biological Data Analysis: Agglomerative Clustering is widely used in bioinformatics for analyzing gene expression data, protein sequence analysis, and clustering biological samples based on their characteristics.

Algorithm 52

Algorithm Computer Vision Categorization Data Analysis 52

Viso.ai

OCTOBER 10, 2024

Pattern Recognition in Data Analysis What is Pattern Recognition? provides Viso Suite , the world’s only end-to-end Computer Vision Platform. The solution enables teams worldwide to develop and deliver custom real-world computer vision applications. How does Pattern Recognition Work? What Is a Pattern?

Neural Network 98

Neural Network Computer Vision Deep Learning Machine Learning 98

Mlearning.ai

JULY 29, 2023

In this article, we present a comprehensive overview of the most commonly used data visualization functions and tools, with a particular focus on their applications in machine learning projects, especially those involving computer vision. What is data visualization? What are popular Python data visualization libraries?

Python 52

Python Categorization Computer Vision Data Science 52

Topbots

DECEMBER 19, 2023

Key takeaways: In the age of Generative AI, we moved from the focus on perception in vision models (i.e., For 20 years, computer vision was focused on benchmark research, which helped to focus on the most prominent problems. The main idea is to use insights from adaptive data analysis.

Computer Vision 52

Computer Vision Natural Language Processing AI Researcher AI Research 52

Viso.ai

JANUARY 16, 2024

Most conventional AI-powered tools only use genre or artist as relevant factors in their training data. This ANN’s training involves understanding and categorizing music based on human perceptions and emotions. Emotional Perception AI Ltd argues that this is going a step beyond conventional categorization.

Neural Network 52

Neural Network Computer Vision Categorization Algorithm 52

Marktechpost

NOVEMBER 17, 2024

Let’s explore its ideal applications and the types of tasks and data it excels at. Key Applications of SVM Text Classification SVM is widely used for categorizing text documents, such as spam email detection or topic classification. SVM works best with well-defined classes, clear decision boundaries, and a moderate amount of data.

Algorithm 104

Algorithm Machine Learning Computer Vision Categorization 104