ODSC - Open Data Science

MARCH 13, 2023

Recently, we posted the first article recapping our recent machine learning survey. There, we talked about some of the results, such as what programming languages machine learning practitioners use, what frameworks they use, and what areas of the field they’re interested in. As the chart shows, two major themes emerged.

Machine Learning 94

Machine Learning Data Science Categorization Python 94

Marktechpost

DECEMBER 22, 2023

Researchers from Lebanese American University and United Arab Emirates University have collaborated to employ artificial intelligence (AI) successfully through the Scale Conjugate Gradient Neural Network (SCJGNN), providing numerical solutions for the language-based learning model. If you like our work, you will love our newsletter.

Deep Learning 57

Deep Learning Categorization Neural Network Artificial Intelligence 57

ODSC - Open Data Science

JULY 26, 2023

As a senior data scientist, I often encounter aspiring data scientists eager to learn about machine learning (ML). In this comprehensive guide, I will demystify machine learning, breaking it down into digestible concepts for beginners. What is Machine Learning?

Machine Learning 52

Machine Learning ML Data Scientist Neural Network 52

Pickl AI

AUGUST 1, 2023

As technology continues to impact how machines operate, Machine Learning has emerged as a powerful tool enabling computers to learn and improve from experience without explicit programming. In this blog, we will delve into the fundamental concepts of data model for Machine Learning, exploring their types.

Machine Learning 52

Machine Learning Neural Network Algorithm Convolutional Neural Networks 52

Pickl AI

JULY 28, 2023

Image Recognition using Machine Learning and MATLAB: With the advent of Machine Learning , it is now possible for computers to recognize and decipher objects, patterns, and other properties in digital photographs. In the early days of computer vision, handcrafted features like edges, corners, and textures were used.

Machine Learning 52

Machine Learning Convolutional Neural Networks Neural Network Deep Learning 52

Heartbeat

DECEMBER 13, 2023

Guide to evaluation metrics for classification in machine learning Photo by Jon Tyson on Unsplash In machine learning, data scientists use evaluation metrics to assess the model's performance in terms of the ability of the various machine learning models to classify the data points into their respective classes accurately.

Machine Learning 52

Machine Learning Data Scientist Deep Learning Categorization 52

IBM Journey to AI blog

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

ESG 203

ESG Categorization Large Language Models NLP 203

Unite.AI

JUNE 2, 2023

Based on this, it makes an educated guess about the importance of incoming emails, and categorizes them into specific folders. In addition to the smart categorization of emails, SaneBox also comes with a feature named SaneBlackHole, designed to banish unwanted emails.

Categorization 261

Categorization Natural Language Processing Automation AI 261

Marktechpost

JANUARY 24, 2024

With the growth of Deep learning, it is used in many fields, including data mining and natural language processing. However, deep neural networks are inaccurate and can produce unreliable outcomes. Then, they used a machine learning algorithm to determine data distribution mismatches based on forward-backward cycles.

Neural Network 106

Neural Network Deep Learning Data Mining Natural Language Processing 106

Viso.ai

DECEMBER 19, 2023

Image Classification Using Machine Learning CNN Image Classification (Deep Learning) Example applications of Image Classification Let’s dive deep into it! AIoT , the combination of AI and IoT, enables the development of highly scalable systems that leverage machine learning for distributed data analysis.

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

Becoming Human

MAY 12, 2023

In what ways do we understand image annotations, the underlying technology behind AI and machine learning (ML), and its importance in developing accurate and adequate AI training data for machine learning models? Overall, it shows the more data you have, the better your AI and machine learning models are.

Machine Learning 81

Machine Learning Computer Vision Automation Artificial Intelligence 81

Marktechpost

MARCH 11, 2024

This obstacle sharply differs from supervised learning, where leveraging cross-entropy classification loss enables reliable scaling to vast networks. In deep learning, classification tasks show effectiveness with large neural networks, while regression tasks can benefit from reframing as classification, enhancing performance.

Neural Network 121

Neural Network Categorization Deep Learning Robotics 121

Marktechpost

APRIL 5, 2024

The proposed approach was explained by analyzing neural network architectures, particularly transformers, from a categorical perspective, specifically utilizing topos theory. While traditional neural networks can be embedded in pretopos categories, transformers necessarily reside in a topos completion.

Neural Network 127

Neural Network Natural Language Processing Categorization Explainability 127

Marktechpost

MAY 18, 2024

Effective graph pooling is essential for downsizing and learning representations, categorized into global and hierarchical pooling. For graph-level classification, pooling operations, categorized into global and hierarchical methods, are crucial. Both face over-smoothing issues, addressed by models like MixHop and N-GCN.

Neural Network 109

Neural Network Categorization Deep Learning Data Analysis 109

AssemblyAI

MAY 14, 2024

It automatically categorizes, summarizes, and extracts actionable insights from customer calls, such as flagging questions and complaints. It uses state-of-the-art deep learning models trained on diverse, large datasets to catch subtle patterns in speech that may indicate depression or anxiety. For example, Corti.ai

Natural Language Processing 147

Natural Language Processing Automation Robotics AI 147

Analytics Vidhya

MARCH 4, 2023

The development of music streaming services has increased the demand for automatic music categorization and recommendation systems. Introduction The music industry has become more popular, and how people listen to music is changing like wildfire.

Categorization 253

Categorization Deep Learning Machine Learning 253

ODSC - Open Data Science

FEBRUARY 6, 2023

You’ll explore statistical and machine learning approaches to anomaly detection, as well as supervised and unsupervised approaches to fraud modeling. Intro to Deep Learning with PyTorch and TensorFlow Dr. Jon Krohn | Chief Data Scientist | Nebula.io

Categorization 98

Categorization Data Science Data Scientist Deep Learning 98

Artificial Corner

JULY 30, 2023

Photo by Shubham Dhage on Unsplash Introduction Large language Models (LLMs) are a subset of Deep Learning. Transformer architectures give a machine learning model the ability to use self-attention mechanisms to recognize links between words in a phrase, independent of where they appear in the text sequence.

Large Language Models 98

Large Language Models LLM Natural Language Processing Deep Learning 98

Marktechpost

JULY 25, 2023

LogAI provides a unified model interface for popular statistical, time-series, and deep-learning models, making it easy to benchmark deep-learning algorithms for log anomaly detection. The Information Extraction Layer of LogAI converts log records into vectors for machine learning.

Deep Learning 95

Deep Learning Machine Learning Algorithm Categorization 95

AssemblyAI

SEPTEMBER 12, 2023

Automatic Speech Recognition, or ASR, is the use of Machine Learning or Artificial Intelligence (AI) technology to process human speech into readable text. In 2014, Baidu published the paper, Deep Speech: Scaling up end-to-end speech recognition. Let’s look more closely at these two dominant approaches to ASR.

Deep Learning 130

Deep Learning Machine Learning Categorization Data Analysis 130

Unite.AI

APRIL 15, 2024

Non-native accents are often associated with lower levels of intelligence , competence, and education; are deemed less pleasant to the ear, and can lead to categorizing speakers into in vs outgroups. Even worse, statements are perceived as less credible when delivered by accented individuals. Lack of training data.

Robotics 124

Robotics AI AI Machine Learning 124

Towards AI

AUGUST 25, 2023

DL Artificial intelligence (AI) is the study of ways to build intelligent programs and machines that can creatively solve problems, which has always been considered a human prerogative. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system.

Software Engineer 96

Software Engineer Machine Learning Neural Network Artificial Intelligence 96

IBM Journey to AI blog

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data. positive, negative or neutral).

Convolutional Neural Networks 144

Convolutional Neural Networks Data Mining Categorization Machine Learning 144

Marktechpost

JULY 17, 2023

The system analyzes visual data before categorizing an object in a photo or video under a predetermined heading. The tool supports various video formats and integrates seamlessly with popular cloud storage providers, ensuring a smooth integration with your existing machine learning pipeline. Identification of the item.

Computer Vision 94

Computer Vision Neural Network Machine Learning Deep Learning 94

Mlearning.ai

AUGUST 3, 2023

Optimizing TFLite Models for On-Edge Machine Learning for Efficiency: A Comparison of Quantization Techniques Introduction In recent years, machine learning models have become increasingly powerful and complex, enabling remarkable advancements in various applications. Obtaining dataset information.

Machine Learning 52

Machine Learning Neural Network Deep Learning Categorization 52

ODSC - Open Data Science

MARCH 13, 2023

They are experts in machine learning, NLP, deep learning, data engineering, MLOps, and data visualization. Learn more about a few of our ODSC East 2023 instructors, their backgrounds in education, and why they’re fit for imparting their knowledge. Dr. Jon Krohn Chief Data Scientist | Nebula.io

Data Science 80

Data Science Software Engineer Deep Learning Machine Learning 80

ODSC - Open Data Science

APRIL 10, 2023

It also explores statistical and machine learning approaches to anomaly detection. Deep Learning with PyTorch and TensorFlow part 1 and 2 Dr. Jon Krohn | Chief Data Scientist | Nebula.io Introduction to scikit-learn: Machine Learning in Python Thomas J. Jon Krohn | Chief Data Scientist | Nebula.io

Software Engineer 52

Software Engineer Categorization Data Science Machine Learning 52

Unite.AI

FEBRUARY 28, 2024

The sheer scale of these models, combined with advanced deep learning techniques, enables them to achieve state-of-the-art performance on language tasks. Classification: LLMs can categorize and label texts for sentiment, topic, authorship and more. Let's examine some prominent attack vectors: 1.

Large Language Models 162

Large Language Models LLM Machine Learning Neural Network 162

Unite.AI

FEBRUARY 26, 2024

In fact, the machine learning (ML) algorithms behind every AI model are trained on vast amounts of data to perform well. Among these cases were lawsuits filed by artists who accused developers of deep learning and text-to-image models such as Stable Diffusion and Midjourney of utilizing their digital art in AI training without consent.

Chatbots 162

Chatbots Categorization ChatGPT Deep Learning 162

Heartbeat

JANUARY 24, 2024

The importance of EDA in the machine learning world is well known to its users. EDA is the first step in every machine learning problem solution. It is most likely the crucial component of a machine learning project. We do the univariate analysis of numerical and categorical variables differently.

Data Analysis 52

Data Analysis Categorization Data Scientist Machine Learning 52

ODSC - Open Data Science

AUGUST 8, 2023

Sessions include, but are not limited to Introduction to Statistics for Data Science An Introduction to Data Wrangling with SQL Introduction to Python for Data Analysis Introduction to Machine Learning Days 2, 3, and 4 will feature sessions for data scientists of all levels from beginner to advanced.

Data Science 52

Data Science Deep Learning Machine Learning Python 52

Mlearning.ai

JULY 17, 2023

It natively supports only numerical data, so typically an encoding is applied first for converting the categorical data into a numerical form. Introduction Clustering Clustering is a fundamental technique in the field of machine learning that aims to group similar data points together based on their inherent characteristics or properties.

Categorization 52

Categorization Algorithm Deep Learning Data Analysis 52

Pickl AI

APRIL 25, 2023

There are five different subsets of Artificial Intelligence which include Machine Learning, Deep Learning, Robotics, Neural Networks, and NLP. What is Machine Learning? There are various Machine Learning algorithms including regression and classification algorithms. What is Deep Learning?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Neural Network Natural Language Processing 52

Marktechpost

DECEMBER 31, 2023

AI, particularly through machine learning and deep learning, has been applied to analyze patient data more effectively. This approach has been particularly useful in identifying and categorizing lesions in various medical conditions, indicating its applicability in TMD diagnosis and management.

Categorization 116

Categorization Algorithm Deep Learning Artificial Intelligence 116

Artificial Corner

JUNE 8, 2023

The answer lies in a fascinating concept called supervised learning. Machine learning can be categorized into supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning, deep learning and so on. Further Readings What is Machine Learning?!

Machine Learning 94

Machine Learning Algorithm Categorization ML 94

Viso.ai

DECEMBER 20, 2023

Viso Suite – End-to-End Computer Vision and No-Code for Computer Vision Teams What is supervised learning and unsupervised learning in computer vision? What is supervised learning? Supervised learning is a type of machine learning algorithm that learns from a set of training data that has been labeled training data.

Computer Vision 98

Computer Vision Neural Network Machine Learning Algorithm 98

AssemblyAI

JANUARY 23, 2024

Large Language Models, or LLMs , are Machine Learning models that understand, generate, and interact with human language.  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. 

Large Language Models 147

Large Language Models Natural Language Processing Categorization Automation 147