IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. Instead of using explicit instructions for performance optimization, ML models rely on algorithms and statistical models that deploy tasks based on data patterns and inferences. What is machine learning?

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Unite.AI

MAY 8, 2024

He began his career at Yandex in 2017, concurrently studying at the Yandex School of Data Analysis. During my school years, I spent a lot of time studying math, probability theory, and statistics, and got an opportunity to play with classical machine learning algorithms such as linear regression and KNN.

Machine Learning 298

Machine Learning Software Engineer Large Language Models Data Analysis 298

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 91

Data Analysis Python Natural Language Processing Computer Vision 91

Marktechpost

NOVEMBER 27, 2024

Machine Learning, a subset of Artificial Intelligence, has emerged as a transformative force, empowering machines to learn from data and make intelligent decisions without explicit programming. At its core, machine learning algorithms seek to identify patterns within data, enabling computers to learn and adapt to new information.

Machine Learning 113

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Unite.AI

SEPTEMBER 21, 2023

Organizations and practitioners build AI models that are specialized algorithms to perform real-world tasks such as image classification, object detection, and natural language processing. As a result, AI improves productivity, reduces human error, and facilitates data-driven decision-making for all stakeholders.

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Convolutional Neural Networks Neural Network Artificial Intelligence Artificial Intelligence 289

AI Weekly

JULY 13, 2023

However, sharing biomedical data can put sensitive personal information at risk. plos.org Screening for Chagas disease from the electrocardiogram using a deep neural network Worldwide, it is estimated that over 6 million people are infected with Chagas disease (ChD). [Try Pluto for free today] pluto.fi

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AI News

OCTOBER 15, 2024

By leveraging vast amounts of data and powerful algorithms, ML enables companies to automate processes, make accurate predictions, and uncover hidden patterns to optimise performance. Unsupervised machine learning systems use artificial neural networks to continue interacting with customers and retain existing customers.

Machine Learning 287

Machine Learning Chatbots Business Intelligence Automation 287

Unite.AI

SEPTEMBER 18, 2023

The above image depicts the architecture of deep learning perceptron, and as it can be seen in the image, a deep learning framework employs a multiple-level neural network architecture to learn the features in the data. The Paillier algorithm works as depicted.

Deep Learning 321

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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.

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Unite.AI

JULY 24, 2024

Over the past decade, advancements in machine learning, Natural Language Processing (NLP), and neural networks have transformed the field. Core ML brought powerful machine learning algorithms to the iOS platform, enabling apps to perform tasks such as image recognition, NLP, and predictive analytics.

Machine Learning 223

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Marktechpost

MAY 5, 2024

Machine Learning with Python This course covers the fundamentals of machine learning algorithms and when to use each of them. The course covers numerous algorithms of supervised and unsupervised learning and also teaches how to build neural networks using TensorFlow. and evaluating the same.

Machine Learning 120

Machine Learning Python Neural Network Convolutional Neural Networks 120

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.

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Marktechpost

JANUARY 30, 2025

This paradigm shift is particularly visible in applications such as: Autonomous Vehicles Self-driving cars and drones rely on perception modules (sensors, cameras) fused with advanced algorithms to operate in dynamic traffic and weather conditions. This process merges data into a single coherent representation.

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Robotics Convolutional Neural Networks Large Language Models AI 116

Marktechpost

MARCH 31, 2024

Whether you’re a beginner, a seasoned data scientist, or someone interested in leveraging data in your work, our carefully selected list of top data science books for 2024 offers a comprehensive guide. The book covers topics like supervised learning, unsupervised learning, neural networks, support vector machines, etc.

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IBM Journey to AI blog

DECEMBER 19, 2023

Common machine learning algorithms for supervised learning include: K-nearest neighbor (KNN) algorithm : This algorithm is a density-based classifier or regression modeling tool used for anomaly detection. Regression modeling is a statistical tool used to find the relationship between labeled data and variable data.

Machine Learning 207

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Marktechpost

APRIL 24, 2024

The increasing complexity of AI systems, particularly with the rise of opaque models like Deep Neural Networks (DNNs), has highlighted the need for transparency in decision-making processes. ELI5 also implements several algorithms for inspecting black-box models. The Institute for Ethical AI & ML maintains the XAI library.

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Explainable AI Explainability Neural Network Data Scientist 117

IBM Journey to AI blog

FEBRUARY 14, 2024

Promote cross- and up-selling Recommendation engines use consumer behavior data and AI algorithms to help discover data trends to be used in the development of more effective up-selling and cross-selling strategies, resulting in more useful add-on recommendations for customers during checkout for online retailers.

Computer Vision 247

Computer Vision Robotics NLP Automation 247

Towards AI

JUNE 19, 2024

Deciding What Algorithm to Use for Earth Observation. Picking the best algorithm is usually tricky or even frustrating. Especially if you do not know what you are looking for, you might utilize an algorithm and get an undesirable outcome, which in turn will take you back to square one. How to determine the right algorithm 1.

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Algorithm Neural Network Business Intelligence Machine Learning 81

Marktechpost

MAY 1, 2024

In contrast, artificial intelligence represents a different paradigm, focusing on specific tasks performed through algorithms, data processing, and machine learning techniques. Fundamental Differences: Human and artificial intelligence differ fundamentally in structure, speed, connectivity, scalability, and energy consumption.

Neural Network 113

Neural Network Artificial Intelligence Artificial Intelligence Explainability 113

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.

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Marktechpost

OCTOBER 10, 2024

Data science is used to guide decision-making and influence business strategies. Key Components of Data Science Data Collection : Gathering raw data from various sources. Data Cleaning : Ensuring the data is usable and accurate. Data Analysis : Applying statistical methods to discover trends.

Data Science 108

Data Science Machine Learning Data Scientist ML Engineer 108

Viso.ai

OCTOBER 10, 2024

Pattern recognition is the ability of machines to identify patterns in data, and then use those patterns to make decisions or predictions using computer algorithms. Pattern Recognition in Data Analysis What is Pattern Recognition? The data inputs can be words or texts, images, or audio files.

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Neural Network Computer Vision Deep Learning Machine Learning 98

Mlearning.ai

MAY 8, 2023

A comprehensive step-by-step guide with data analysis, deep learning, and regularization techniques Introduction In this article, we will use different deep-learning TensorFlow neural networks to evaluate their performances in detecting whether cell nuclei mass from breast imaging is malignant or benign. perimeter d.

Neural Network 52

Neural Network Deep Learning Machine Learning Data Analysis 52

Viso.ai

DECEMBER 19, 2023

Today, the use of convolutional neural networks (CNN) is the state-of-the-art method for image classification. AIoT , the combination of AI and IoT, enables the development of highly scalable systems that leverage machine learning for distributed data analysis. How Does Image Classification Work?

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Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

Marktechpost

AUGUST 9, 2024

The release of Trinity-2-Codestral-22B addresses the growing need for more efficient and scalable computational power in an era of exponentially increasing data processing demands. Trinity-2-Codestral-22B is an upgrade from its predecessor and a reimagined system that integrates cutting-edge algorithms with enhanced processing capabilities.

Neural Network 119

Neural Network Machine Learning Algorithm Data Analysis 119

Pickl AI

AUGUST 27, 2024

Summary: Python simplicity, extensive libraries like Pandas and Scikit-learn, and strong community support make it a powerhouse in Data Analysis. It excels in data cleaning, visualisation, statistical analysis, and Machine Learning, making it a must-know tool for Data Analysts and scientists. Why Python?

Data Analysis 52

Data Analysis Python Machine Learning Data Mining 52

Unite.AI

JULY 25, 2024

The 1990s saw significant improvements in statistical machine translation as models learned from vast amounts of bilingual data, leading to better translations. A significant breakthrough came with neural networks and deep learning. IBM's Model 1 and Model 2 laid the groundwork for advanced systems. Deploying Llama 3.1

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Neural Network AI AI Machine Learning 202

Pickl AI

AUGUST 3, 2023

Introduction to Deep Learning Algorithms: Deep learning algorithms are a subset of machine learning techniques that are designed to automatically learn and represent data in multiple layers of abstraction. Each node receives input data, performs calculations, and passes the results to nodes in the subsequent layer.

Deep Learning 52

Deep Learning Machine Learning Algorithm Neural Network 52

Marktechpost

JULY 30, 2024

This innovative approach focuses on two key functions: decomposing state-of-the-art Graph Neural Networks (GNNs), LLMs, and Table Neural Networks (TNNs) into standardized modules, and enabling the construction of robust models through a “combine, align, and co-train” methodology.

Large Language Models 109

Large Language Models Neural Network Software Engineer Data Analysis 109

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?

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Data Analysis Data Mining Data Discovery Machine Learning 52

ODSC - Open Data Science

FEBRUARY 13, 2023

The field of data science changes constantly, and some frameworks, tools, and algorithms just can’t get the job done anymore. How Deep Neural Networks Work and How We Put Them to Work at Facebook Deep learning is the technology driving today’s artificial intelligence boom.

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Marktechpost

JULY 3, 2023

Predictive Analytics relies more specifically on using data, statistical algorithms, and machine learning techniques to forecast future outcomes based on historical and real-time data. Predictive Analytics utilizes various machine learning algorithms to build predictive models that can provide insights into future scenarios.

Deep Learning 125

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IBM Journey to AI blog

JUNE 14, 2023

Artificial intelligence (AI) One of the most significant benefits of AI technology in smart manufacturing is its ability to conduct real-time data analysis efficiently. Companies can also use AI systems to identify anomalies and equipment defects.

Robotics 227

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Mlearning.ai

MAY 5, 2023

These models, which are based on artificial intelligence and machine learning algorithms, are designed to process vast amounts of natural language data and generate new content based on that data. It wasn’t until the development of deep learning algorithms in the 2000s and 2010s that LLMs truly began to take shape.

Large Language Models 98

Large Language Models Neural Network Natural Language Processing Deep Learning 98

Artificial Corner

SEPTEMBER 27, 2024

Projects for beginners: Automate 4 Boring Tasks in Python with 5 Lines of Code How to Automate Emails with Python Stage 2: Python for Data Analysis This is what I call the “essential Python stuff to work with data.” At this stage, projects usually involve all the data analysis libraries mentioned before.

Python 98

Python ML Machine Learning Data Analysis 98

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

IBM Journey to AI blog

JULY 6, 2023

Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis. Machine learning works on a known problem with tools and techniques, creating algorithms that let a machine learn from data through experience and with minimal human intervention.

Data Science 175

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