IBM Journey to AI blog

DECEMBER 20, 2023

Many retailers’ e-commerce platforms—including those of IBM, Amazon, Google, Meta and Netflix—rely on artificial neural networks (ANNs) to deliver personalized recommendations. They’re also part of a family of generative learning algorithms that model the input distribution of a given class or/category.

Machine Learning 230

Machine Learning Neural Network Algorithm Computer Vision 230

Marktechpost

MAY 5, 2024

The course covers numerous algorithms of supervised and unsupervised learning and also teaches how to build neural networks using TensorFlow. Students learn to implement and analyze models like linear models, kernel machines, neural networks, and graphical models.

Machine Learning 120

Machine Learning Python Neural Network Convolutional Neural Networks 120

Pickl AI

JANUARY 26, 2025

Introduction Deep Learning models transform how we approach complex problems, offering powerful tools to analyse and interpret vast amounts of data. These models mimic the human brain’s neural networks, making them highly effective for image recognition, natural language processing, and predictive analytics.

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 52

AI News

OCTOBER 15, 2024

Unsupervised machine learning systems use artificial neural networks to continue interacting with customers and retain existing customers. Speed and efficiency : Chatbots and virtual assistants can process information quicker than humans and eliminate wait times for customers.

Machine Learning 288

Machine Learning Chatbots Business Intelligence Automation 288

Pickl AI

SEPTEMBER 3, 2024

Summary: Artificial Neural Network (ANNs) are computational models inspired by the human brain, enabling machines to learn from data. Introduction Artificial Neural Network (ANNs) have emerged as a cornerstone of Artificial Intelligence and Machine Learning , revolutionising how computers process information and learn from data.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 52

Mlearning.ai

MAY 30, 2023

Recurrent Neural Networks (RNNs) have become a potent tool for analysing sequential data in the large subject of artificial intelligence and machine learning. As we know that Convolutional Neural Network (CNN) is used for structured arrays of data such as image data. RNN is used for sequential data.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 52

Unite.AI

SEPTEMBER 18, 2023

Artificial Intelligence is a very vast branch in itself with numerous subfields including deep learning, computer vision , natural language processing , and more. The neural network consists of three types of layers including the hidden layer, the input payer, and the output layer.

Deep Learning 321

Deep Learning Artificial Intelligence Artificial Intelligence AI 321

Unite.AI

JULY 24, 2024

Over the past decade, advancements in machine learning, Natural Language Processing (NLP), and neural networks have transformed the field. The company ensures that all AI processes are conducted on-device, meaning that user data never leaves the device unless explicitly allowed by the user.

Machine Learning 223

Machine Learning NLP AI AI 223

Marktechpost

JANUARY 30, 2025

The consistent theme in these use cases is an AI-driven entity that moves beyond passive data analysis to dynamically and continuously sense, think, and act. Yet, before a system can take meaningful action, it must capture and interpret the data from which it forms its understanding.

Robotics 116

Robotics Convolutional Neural Networks Large Language Models AI 116

Heartbeat

FEBRUARY 8, 2023

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

Natural Language Processing 52

Natural Language Processing NLP Machine Learning Deep Learning 52

Marktechpost

OCTOBER 23, 2024

From the statistical foundations of machine learning to the complex algorithms powering neural networks, mathematics plays a pivotal role in shaping the capabilities and limitations of AI. Derivatives are key to optimizing functions like the loss function in neural networks by measuring rates of change.

Neural Network 116

Neural Network Algorithm Robotics Machine Learning 116

Artificial Corner

JANUARY 23, 2025

2 Python for Data Analysis Course This one is more like a playlist than a course; however, you will find more useful lectures in this playlist than in some paid courses. The first 8 videos in the playlist make a 10-hour data analysis course. 4 Machine Learning & Artificial Intelligence with Tensorflow 2.0

Data Science 95

Data Science Python Convolutional Neural Networks Natural Language Processing 95

Marktechpost

MAY 29, 2024

Image Source Traditional GPUs execute neural network models in a kernel-by-kernel fashion. This constant context switching and data shuffling increase latency and result in underutilization. Each layer’s kernel is loaded and executed, and its results are returned to memory before moving on to the next layer.

Neural Network 104

Neural Network Natural Language Processing Automation Data Analysis 104

Heartbeat

MARCH 22, 2023

Learn NLP data processing operations with NLTK, visualize data with Kangas , build a spam classifier, and track it with Comet Machine Learning Platform Photo by Stephen Phillips — Hostreviews.co.uk Many data we analyze as data scientists consist of a corpus of human-readable text.

Natural Language Processing 52

Natural Language Processing NLP Deep Learning Machine Learning 52

Mlearning.ai

MAY 5, 2023

However, these early systems were limited in their ability to handle complex language structures and nuances, and they quickly fell out of favor. In the 1980s and 1990s, the field of natural language processing (NLP) began to emerge as a distinct area of research within AI.

Large Language Models 98

Large Language Models Neural Network Natural Language Processing Deep Learning 98

Viso.ai

JANUARY 2, 2024

In the following, we will explore Convolutional Neural Networks (CNNs), a key element in computer vision and image processing. Whether you’re a beginner or an experienced practitioner, this guide will provide insights into the mechanics of artificial neural networks and their applications. Howard et al.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

Marktechpost

NOVEMBER 10, 2023

Traditionally, Convolutional Neural Networks (CNNs) have been the go-to models for processing image data, leveraging their ability to extract meaningful features and classify visual information.

Convolutional Neural Networks 109

Convolutional Neural Networks Computer Vision Natural Language Processing Neural Network 109

Unite.AI

FEBRUARY 23, 2024

Here, learners delve into the art of crafting prompts for large language models like ChatGPT, learning how to leverage their capabilities for a range of applications. The second course, “ChatGPT Advanced Data Analysis,” focuses on automating tasks using ChatGPT's code interpreter.

Prompt Engineering 272

Prompt Engineering Prompt Engineer Large Language Models ChatGPT 272

Becoming Human

MARCH 17, 2023

You are most likely to encounter voice command devices in the areas of customer service, voice-to-text dictation, email management, data analysis, help desk management, and team collaboration. Conversational capabilities and emotional intelligence are at the core of virtual assistants that hold promise for the future.

Neural Network 124

Neural Network Artificial Intelligence Artificial Intelligence Automation 124

Viso.ai

OCTOBER 10, 2024

Pattern Recognition in Data Analysis What is Pattern Recognition? In supervised learning, images are annotated to train neural networks – Image Annotation with Viso Suite What Is the Goal of Pattern Recognition? How does Pattern Recognition Work? Pattern Recognition Projects and Use Cases About us: viso.ai

Neural Network 98

Neural Network Computer Vision Deep Learning Machine Learning 98

Marktechpost

NOVEMBER 27, 2024

Sigmoid Kernel: Inspired by neural networks. sentiment analysis). 5) K-Means Clustering K-means clustering is a popular unsupervised machine learning algorithm used for grouping similar data points. It’s a fundamental technique for exploratory data analysis and pattern recognition. facial recognition).

Machine Learning 113

Machine Learning Algorithm Neural Network Convolutional Neural Networks 113

Marktechpost

MAY 10, 2024

It explores various models like linear, xgboost, and neural networks to analyze stock data and make predictions. Introduction to Machine Learning for Finance This course covers foundational machine learning concepts in banking, focusing on data analysis tailored for financial data.

Machine Learning 103

Machine Learning Python Neural Network Deep Learning 103

ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. In a change from last year, there’s also a higher demand for those with data analysis skills as well.

NLP 111

NLP Data Science Deep Learning BERT 111

Towards AI

JUNE 27, 2023

For instance, today’s machine learning tools are pushing the boundaries of natural language processing, allowing AI to comprehend complex patterns and languages. Scikit Learn Scikit Learn is a comprehensive machine learning tool designed for data mining and large-scale unstructured data analysis.

Machine Learning 98

Machine Learning ML Neural Network Natural Language Processing 98

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 132

AI Tools Data Science Machine Learning Data Analysis 132

IBM Journey to AI blog

FEBRUARY 14, 2024

Voice-based queries use natural language processing (NLP) and sentiment analysis for speech recognition so their conversations can begin immediately. Running on neural networks , computer vision enables systems to extract meaningful information from digital images, videos and other visual inputs.

Computer Vision 247

Computer Vision NLP Robotics Automation 247

John Snow Labs

MAY 23, 2023

Visual question answering (VQA), an area that intersects the fields of Deep Learning, Natural Language Processing (NLP) and Computer Vision (CV) is garnering a lot of interest in research circles. A VQA system takes free-form, text-based questions about an input image and presents answers in a natural language format.

Natural Language Processing 40

Natural Language Processing Deep Learning NLP Convolutional Neural Networks 40

ODSC - Open Data Science

AUGUST 31, 2023

The moment a cybercriminal drafts a strategy for avoiding counterfeit detectors, industry professionals reinforce them, making blockchain stronger to track and natural language processing more proficient at spotting textual inconsistencies. The relationship between AI and experts must remain strong.

Natural Language Processing 98

Natural Language Processing Data Scientist Neural Network Data Science 98

Marktechpost

JULY 3, 2023

The preparatory expert phase can be flexibly managed by internal or external resources with data science expertise , such as the Neural Concept team. ML refers to the development of algorithms that enable computers to learn from data without explicit programming.

Deep Learning 125

Deep Learning Machine Learning Neural Network Artificial Intelligence 125

Viso.ai

DECEMBER 1, 2023

A deep learning model, or a DL model, is a neural network that has been trained to learn how to perform a task, such as recognizing objects in digital images and videos, or understanding human speech. Deep learning models are trained by using large sets of data and algorithms that enable the model to learn how to perform the task.

AI Modeling 98

AI Modeling Neural Network Deep Learning Computer Vision 98

Towards AI

AUGUST 25, 2023

Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system. There is often confusion between the terms artificial intelligence and machine learning, which is discussed in The AI Process. Join thousands of data leaders on the AI newsletter.

Machine Learning 98

Machine Learning Software Engineer Neural Network Data Science 98

IBM Journey to AI blog

OCTOBER 20, 2023

These development platforms support collaboration between data science and engineering teams, which decreases costs by reducing redundant efforts and automating routine tasks, such as data duplication or extraction. As one would expect, these changes and growing demands have led to mounting provider frustration and burnout.

Machine Learning 225

Machine Learning Automation AI AI 225

Chatbots Life

APRIL 16, 2024

Variational Autoencoders (VAEs) : VAEs are neural networks that learn the underlying distribution of the input data and generate new data points. They map input data to a latent space, which is used to reconstruct the input or generate new data points. This is useful in natural language processing tasks.

Neural Network 59

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 59

IBM Journey to AI blog

JULY 6, 2023

Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis.

Data Science 175

Data Science Machine Learning Big Data Data Mining 175

IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Machine learning algorithms like Naïve Bayes and support vector machines (SVM), and deep learning models like convolutional neural networks (CNN) are frequently used for text classification.

Data Mining 170

Data Mining Convolutional Neural Networks Categorization Machine Learning 170

Pickl AI

AUGUST 1, 2023

Text mining is also known as text analytics or Natural Language Processing (NLP). It is the process of deriving valuable patterns, trends, and insights from unstructured textual data. Visualize the sentiment distribution and analyze trends and patterns in the data.

Data Analysis 52

Data Analysis Python Categorization Data Mining 52

Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. At the same time, Keras is a high-level neural network API that runs on top of TensorFlow and simplifies the process of building and training deep learning models.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Neural Network 52