IBM Journey to AI blog

AUGUST 28, 2023

As it pertains to social media data, text mining algorithms (and by extension, text analysis) allow businesses to extract, analyze and interpret linguistic data from comments, posts, customer reviews and other text on social media platforms and leverage those data sources to improve products, services and processes.

Data Mining 170

Data Mining Convolutional Neural Networks Categorization Machine Learning 170

Chatbots Life

MAY 16, 2024

IF THERE IS A SIN, THIS IS THE ONLY SIN; TO SAY THAT YOU ARE WEAK, OR OTHERS ARE WEAK” - By Swami Vivekanand Is Deep Learning now overtaking the Machine Learning algorithm? As we know to perform any Machine Learning algorithm we require a humongous amount of data and very high computation power. Famous Deep Learning Networks.

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network Machine Learning 52

Marktechpost

JANUARY 15, 2025

Technical Details and Benefits Deep learning relies on artificial neural networks composed of layers of interconnected nodes. Notable architectures include: Convolutional Neural Networks (CNNs): Designed for image and video data, CNNs detect spatial patterns through convolutional operations.

Deep Learning 87

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 87

Topbots

OCTOBER 4, 2023

Generated with Bing and edited with Photoshop Predictive AI has been driving companies’ ROI for decades through advanced recommendation algorithms, risk assessment models, and fraud detection tools. The predictive AI algorithms can be used to predict a wide range of variables, including continuous variables (e.g.,

Generative AI 119

Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 119

Marktechpost

JUNE 27, 2023

The system’s adaptability makes it useful in many contexts, including but not limited to customer care, virtual agents, and chatbots. Using sophisticated algorithms, it can determine where an object’s borders are and then either replace the background with a translucent one or eliminate it.

AI Tools 103

AI Tools Convolutional Neural Networks Artificial Intelligence Artificial Intelligence 103

Chatbots Life

APRIL 16, 2024

Examples of Generative Models Generative models encompass various algorithms that capture patterns in data to generate realistic new examples. Examples of Discriminative Models Discriminative models encompass a range of algorithms that excel in diverse tasks such as classification and sequence analysis.

Neural Network 59

Neural Network Convolutional Neural Networks Natural Language Processing Machine Learning 59

Heartbeat

NOVEMBER 21, 2023

From object detection and recognition to natural language processing, deep reinforcement learning, and generative models, we will explore how deep learning algorithms have conquered one computer vision challenge after another. One of the most significant breakthroughs in this field is the convolutional neural network (CNN).

Computer Vision 52

Computer Vision Deep Learning NLP Neural Network 52

Chatbots Life

OCTOBER 9, 2023

Researchers are using microwave imaging and convolutional neural networks for breast cancer screening with high accuracy in classifying profiles as healthy or diseased. ? was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Deep Learning Generative AI 52

Viso.ai

DECEMBER 21, 2023

From the development of sophisticated object detection algorithms to the rise of convolutional neural networks (CNNs) for image classification to innovations in facial recognition technology, applications of computer vision are transforming entire industries.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

How to Learn Machine Learning

AUGUST 15, 2024

Projects to Tackle for Your Machine Learning Portfolio To build a comprehensive portfolio, consider including projects from various domains and complexity levels: Image Classification : Develop a model to classify images using convolutional neural networks (CNNs).

Machine Learning 64

Machine Learning Convolutional Neural Networks Neural Network Artificial Intelligence 64

Heartbeat

MAY 30, 2023

The agent is a machine learning algorithm that adapts to take actions in the environment that optimize its total reward. The agent receives an observation from the environment and processes it through a neural network, which generates an action according to its current state. Both GANs and DRL involve learning through feedback.

Neural Network 72

Neural Network Convolutional Neural Networks Deep Learning Machine Learning 72

Viso.ai

JANUARY 24, 2025

Narrow AI chatbots, for instance, are very good at responding to pre-formulated queries, but they have trouble with intricate, open-ended discussions. Architecture of LeNet5 – Convolutional Neural Network – Source The capacity of AGI to generalize and adapt across a broad range of tasks and domains is one of its primary features.

Convolutional Neural Networks 59

Convolutional Neural Networks Neural Network Deep Learning Large Language Models 59

Pickl AI

AUGUST 14, 2024

Neural networks come in various forms, each designed for specific tasks: Feedforward Neural Networks (FNNs) : The simplest type, where connections between nodes do not form cycles. This capability makes them particularly effective for tasks such as image and speech recognition, where traditional algorithms may struggle.

Neural Network 52

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

Pickl AI

JANUARY 15, 2023

A subset of Machine Learning makes use of artificial neural networks and computer algorithms to imitate human learning. In order to improve the outcome of every task, Deep Learning uses machine learning algorithms to perform tasks repeatedly. Having more than three layers, the networks connect effectively with every node.

Deep Learning 52

Deep Learning Neural Network Convolutional Neural Networks Machine Learning 52

Heartbeat

JANUARY 12, 2023

Other practical examples of deep learning include virtual assistants, chatbots, robotics, image restoration, NLP (Natural Language Processing), and so on. Deep learning does this via a multi-layered neural network algorithmic framework. Or how do autonomous vehicles even become a possibility?

Deep Learning 52

Deep Learning Convolutional Neural Networks Neural Network Machine Learning 52

Heartbeat

DECEMBER 8, 2023

Agents can be used for applications such as personal assistants, question answering, chatbots, querying tabular data, interacting with APIs, extraction, summarization, and evaluation. This includes cleaning and transforming data, performing calculations, or applying machine learning algorithms.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Deep Learning LLM 52

Pickl AI

APRIL 9, 2025

A simple example could be an early chess-playing program that evaluated moves based on predefined rules and search algorithms. Instead of hard-coding rules, ML algorithms are designed to learn patterns and make predictions or decisions based on data they are “trained” on. This led to the rise of Machine Learning (ML).

Deep Learning 52

Deep Learning Artificial Intelligence Artificial Intelligence Explainability 52

Viso.ai

FEBRUARY 25, 2023

Vision Transformer (ViT) have recently emerged as a competitive alternative to Convolutional Neural Networks (CNNs) that are currently state-of-the-art in different image recognition computer vision tasks. For example, the popular ChatGPT AI chatbot is a transformer-based language model.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Viso.ai

MARCH 26, 2024

Arguably, one of the most pivotal breakthroughs is the application of Convolutional Neural Networks (CNNs) to financial processes. 4: Algorithmic Trading and Market Analysis No.5: 4: Algorithmic Trading and Market Analysis No.5: In this article, we present 7 key applications of computer vision in finance: No.1:

Computer Vision 52

Computer Vision Neural Network Machine Learning Convolutional Neural Networks 52

Pickl AI

SEPTEMBER 25, 2024

Medical Image Analysis Deep Learning algorithms analyse medical images such as X-rays, MRIs, and CT scans to detect anomalies like tumours or fractures. Algorithmic Trading AI-driven trading systems use Deep Learning to analyse market trends and execute trades at optimal times.

Deep Learning 52

Deep Learning Algorithm Convolutional Neural Networks Neural Network 52

Pickl AI

JULY 14, 2023

Evolution of AI The evolution of Artificial Intelligence (AI) spans several decades and has witnessed significant advancements in theory, algorithms, and applications. Deep Learning, a subfield of ML, gained attention with the development of deep neural networks.

Neural Network 52

Neural Network Software Engineer Artificial Intelligence Artificial Intelligence 52

Pickl AI

AUGUST 1, 2024

Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms. They work on complex problems that require advanced neural networks to analyse vast amounts of data.

Deep Learning 52

Deep Learning Neural Network Machine Learning Natural Language Processing 52

Pickl AI

NOVEMBER 13, 2024

Understanding Backpropagation Backpropagation, short for “backward propagation of errors,” is a core algorithm for training artificial neural networks. It efficiently calculates the gradient of the loss function concerning the network’s weights. Update weights and biases using an optimisation algorithm (e.g.,

Neural Network 52

Neural Network Algorithm Convolutional Neural Networks Natural Language Processing 52

Pickl AI

SEPTEMBER 18, 2023

Models like Generative Adversarial Networks (GANs) can create realistic-looking photos, paintings, and even deepfake films, which are employed in image production jobs. These algorithms learn from massive datasets and then generate fresh material that resembles the training data. from horses to zebras) while preserving their content.

Generative AI 52

Generative AI Neural Network Artificial Intelligence Artificial Intelligence 52

Viso.ai

JULY 9, 2024

To understand how transfer learning works, it is essential to understand the architecture of Deep Neural Networks. Neural Networks are the most widely used algorithm to build ML models for many advanced tasks, as they have shown higher performance accuracy than traditional algorithms.

Neural Network 52

Neural Network BERT Deep Learning Computer Vision 52

Explosion

AUGUST 3, 2017

Supervised learning algorithms have been improving quickly, leading many people to anticipate a new wave of entirely un supervised algorithms : algorithms so “advanced” they can compute whatever you want, without you specifying what that might be. The model is a convolutional neural network stacked with a unigram bag-of-words.

Python 52

Python Convolutional Neural Networks Machine Learning Algorithm 52

Pickl AI

SEPTEMBER 23, 2024

Backpropagation: This algorithm adjusts the neural network’s weights during training by calculating the error at the output layer and propagating it backwards through the network, optimising the model. In image recognition, Convolutional Neural Networks (CNNs) can accurately identify objects and faces in images.

Deep Learning 52

Deep Learning Neural Network Natural Language Processing Convolutional Neural Networks 52

Snorkel AI

MARCH 1, 2023

Chatbots and virtual assistants ChatGPT demonstrated that foundation models can serve as the seed for competent chat bots and virtual assistants that may help businesses provide customer support and answer common questions. It is based on GPT and uses machine learning algorithms to generate code suggestions as developers write.

BERT 83

BERT Natural Language Processing Large Language Models NLP 83

ML Review

JUNE 4, 2018

These new approaches generally; Feed the image into a Convolutional Neural Network (CNN) for encoding, and run this encoding into a decoder Recurrent Neural Network (RNN) to generate an output sentence. Finally, one can use a sentence similarity evaluation metric to evaluate the algorithm.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

Mlearning.ai

JUNE 8, 2023

Use algorithm to determine closeness/similarity of points. Images can be embedded using models such as convolutional neural networks (CNNs) , Examples of CNNs include VGG , and Inception. Knowledge graph embedding algorithms have become a powerful tool for representing and reasoning about complex structured data.

Machine Learning 52

Machine Learning BERT Neural Network OpenAI 52

Mlearning.ai

DECEMBER 13, 2023

The field is complex, covering various algorithms, techniques, and best practices that one needs to understand in depth. Describe the architecture of a Convolutional Neural Network (CNN) in detail. Convolutional Layers: They apply filters to the input image to detect features like edges and corners.

Deep Learning 52

Deep Learning Neural Network Explainability Convolutional Neural Networks 52