Marktechpost

NOVEMBER 30, 2023

Researchers from Lund University and Halmstad University conducted a review on explainable AI in poverty estimation through satellite imagery and deep machine learning. The review underscores the significance of explainability for wider dissemination and acceptance within the development community.

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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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Pickl AI

AUGUST 14, 2024

Summary: Neural networks are a key technique in Machine Learning, inspired by the human brain. They consist of interconnected nodes that learn complex patterns in data. This architecture allows neural networks to learn complex patterns and relationships within data.

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Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 52

IBM Journey to AI blog

AUGUST 9, 2024

Most generative AI models start with a foundation model , a type of deep learning model that “learns” to generate statistically probable outputs when prompted. These adversarial AI algorithms encourage the model to generate increasingly high-quality outputs.

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Pickl AI

AUGUST 1, 2024

Summary : Deep Learning engineers specialise in designing, developing, and implementing neural networks to solve complex problems. Introduction Deep Learning engineers are specialised professionals who design, develop, and implement Deep Learning models and algorithms.

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Deep Learning Neural Network Machine Learning Natural Language Processing 52

Unite.AI

JANUARY 12, 2024

The Evolution of AI Research As capabilities have grown, research trends and priorities have also shifted, often corresponding with technological milestones. The rise of deep learning reignited interest in neural networks, while natural language processing surged with ChatGPT-level models.

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Heartbeat

NOVEMBER 27, 2023

Deep learning automates and improves medical picture analysis. Convolutional neural networks (CNNs) can learn complicated patterns and features from enormous datasets, emulating the human visual system. Convolutional Neural Networks (CNNs) Deep learning in medical image analysis relies on CNNs.

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Marktechpost

JULY 6, 2023

On the other hand, explainable AI models are very complicated deep learning models that are too complex for humans to understand without the aid of additional methods. This is why when Explainable AI models can give a clear idea of why a decision was made but not how it arrived at that decision.

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IBM Journey to AI blog

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

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Viso.ai

FEBRUARY 12, 2024

True to its name, Explainable AI refers to the tools and methods that explain AI systems and how they arrive at a certain output. Artificial Intelligence (AI) models assist across various domains, from regression-based forecasting models to complex object detection algorithms in deep learning.

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Marktechpost

MAY 12, 2024

It is based on adjustable and explainable AI technology. The technology provides automated, improved machine-learning techniques for fraud identification and proactive enforcement to reduce fraud and block rates. CorgiAI CorgiAI is a fraud detection and prevention tool designed to increase income and reduce losses due to fraud.

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AI Tools Neural Network Artificial Intelligence Artificial Intelligence 103

NVIDIA

DECEMBER 13, 2023

Financial Services Firms Embrace AI for Identity Verification The financial services industry is developing AI for identity verification. Harnessing Graph Neural Networks and NVIDIA GPUs GNNs have been embraced for their ability to reveal suspicious activity.

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Marktechpost

AUGUST 24, 2023

r/neuralnetworks The Subreddit is about Deep Learning, Artificial Neural Networks, and Machine Learning. members and is a great place to learn more about the latest AI. It has over 37.4k members and has active discussions on various ML topics. It has over 21.8k

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Pickl AI

JANUARY 13, 2025

We aim to guide readers in choosing the best resources to kickstart their AI learning journey effectively. From neural networks to real-world AI applications, explore a range of subjects. Many books offer hands-on exercises and coding examples for effective learning. Encourages hands-on learning.

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Pickl AI

JULY 14, 2023

Machine Learning and Neural Networks (1990s-2000s): Machine Learning (ML) became a focal point, enabling systems to learn from data and improve performance without explicit programming. Techniques such as decision trees, support vector machines, and neural networks gained popularity.

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Pickl AI

SEPTEMBER 17, 2024

What Is the Difference Between Artificial Intelligence, Machine Learning, And Deep Learning? Artificial Intelligence (AI) is a broad field that encompasses the development of systems capable of performing tasks that typically require human intelligence, such as learning, problem-solving, and decision-making.

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Viso.ai

MARCH 26, 2024

Initially, AI’s role in finance was limited to basic computational tasks. With advancements in machine learning (ML) and deep learning (DL), AI has begun to significantly influence financial operations. It uses neural networks and decision trees for a comprehensive approach to risk evaluation.

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ODSC - Open Data Science

FEBRUARY 25, 2025

Topics Include: Advanced ML Algorithms & EnsembleMethods Hyperparameter Tuning & Model Optimization AutoML & Real-Time MLSystems Explainable AI & EthicalAI Time Series Forecasting & NLP Techniques Who Should Attend: ML Engineers, Data Scientists, and Technical Practitioners working on production-level ML solutions.

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Data Scientist Machine Learning Large Language Models ML Engineer 52

Pickl AI

AUGUST 28, 2024

Examples include Logistic Regression, Support Vector Machines (SVM), Decision Trees, and Artificial Neural Networks. Lazy Learners These algorithms do not build a model immediately from the training data. Instead, they memorise the training data and make predictions by finding the nearest neighbour.

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Viso.ai

JULY 9, 2024

Discriminative models include a wide range of models, like Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), Support Vector Machines (SVMs), or even simpler models like random forests. However, generative AI models are a different class of deep learning.

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Pickl AI

JULY 24, 2024

AI in the 21st Century The 21st century has witnessed an unprecedented boom in AI research and applications. The advent of big data, coupled with advancements in Machine Learning and deep learning, has transformed the landscape of AI. 2011: IBM Watson defeats Ken Jennings on the quiz show “Jeopardy!

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ODSC - Open Data Science

DECEMBER 17, 2024

For example, AI-based lending tools could disproportionately deny loans to minority groups , even if unintentionally. Many AI models, especially deep learning systems, are black boxes with opaque decision-making processes. Transparency is another issue.

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Ofemwire

MARCH 1, 2024

D – Deep Learning : A subset of machine learning where artificial neural networks, algorithms inspired by the human brain, learn from large amounts of data. Deep learning networks can automatically learn to represent patterns in the data with multiple levels of abstraction.

Neural Network 52

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Pickl AI

JULY 1, 2024

Neural Networks Inspired by the human brain, artificial neural networks learn complex relationships within data for highly accurate demand forecasting, especially with vast datasets. Ensemble Learning Combine multiple forecasting models (e.g., Incorporating External Data Integrate external data sources (e.g.,

Data Science 52

Data Science Neural Network Machine Learning Categorization 52

Viso.ai

DECEMBER 6, 2023

Our solution enables leading companies to use a variety of machine learning models and tasks for their computer vision systems. Real-Time Computer Vision: With the help of advanced AI hardware , computer vision solutions can analyze real-time video feeds to provide critical insights. Get a demo here.

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Computer Vision Convolutional Neural Networks Neural Network Categorization 52

The MLOps Blog

JUNE 27, 2023

With extensive language support and integration with major deep learning frameworks, the Model Hub simplifies the integration of pre-trained models and libraries into existing workflows, making it a valuable resource for researchers, developers, and data scientists. Monitor the performance of machine learning models.

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Heartbeat

SEPTEMBER 13, 2023

Through the explainability of AI systems, it becomes easier to build trust, ensure accountability, and enable humans to comprehend and validate the decisions made by these models. For example, explainability is crucial if a healthcare professional uses a deep learning model for medical diagnoses. Russell, C. &

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Defined.ai blog

AUGUST 10, 2023

Emerging Trends in AI and Financial Data Analysis In the fast-evolving field of AI, new trends are constantly emerging, and financial data analysis is no exception. Let’s look at a few trends shaping the future of data analysis using AI.

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Business Intelligence Data Analysis Neural Network Data Quality 52

Pickl AI

SEPTEMBER 17, 2024

Some of the key future trends include: Increased Use of Deep Learning and Neural Networks As computing power and data availability continue to grow, we can expect to see more advanced Deep Learning models being applied to cybersecurity challenges, enabling even more accurate threat detection and prediction.

Machine Learning 52

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Dlabs.ai

MAY 22, 2022

Here, we’ll focus more on his AI courses, particularly the one on ML (one of the most popular and highly-rated Machine Learning online courses around). Once complete, you’ll know all about machine learning, statistics, neural networks, and data mining.

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Mlearning.ai

JANUARY 26, 2023

When it comes to implementing any ML model, the most difficult question asked is how do you explain it. Suppose, you are a data scientist working closely with stakeholders or customers, even explaining the model performance and feature selection of a Deep learning model is quite a task. How do we deal with this?

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Explainability Neural Network Machine Learning AI 52

Pickl AI

NOVEMBER 18, 2024

Neural networks are powerful for complex tasks, such as image recognition or NLP, but may require more computational resources. Neural networks , while flexible and capable of handling large-scale data, require a lot of data and computing power. Different algorithms are suited to different tasks.

Machine Learning 52

Machine Learning Algorithm Data Quality Neural Network 52

Mlearning.ai

FEBRUARY 6, 2023

Classifiers based on neural networks are known to be poorly calibrated outside of their training data [3]. Additionally, multiple different models could be trained to identify AI-Generated Text in different subject matters, reducing the need for generalization. This is why we need Explainable AI (XAI).

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IBM Journey to AI blog

SEPTEMBER 3, 2024

Bias Humans are innately biased, and the AI we develop can reflect our biases. These systems inadvertently learn biases that might be present in the training data and exhibited in the machine learning (ML) algorithms and deep learning models that underpin AI development.

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Mlearning.ai

FEBRUARY 2, 2023

In this article, I show how a Convolutional Neural Network can be used to predict a person's age based on the person's ECG Attia et al 2019 [1], showed that a person's age could be predicted from an ECG using convolutional neural networks (CNN). InceptionTime: Finding AlexNet for Time Series Classification.

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The MLOps Blog

AUGUST 11, 2023

More specifically, embeddings enable neural networks to consume training data in formats that allow extracting features from the data, which is particularly important in tasks such as natural language processing (NLP) or image recognition. Within the context of machine learning, embeddings play a significant role in a number of areas.

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Viso.ai

JANUARY 21, 2025

Generative AI Applications in 2025 Vision Transformers (ViTs) Now, heres something exciting to the computer vision trend in 2025: Vision Transformers. Vision Transformers (ViTs) are neural network architectures that process images using self-attention mechanisms. Theyre becoming essential. Thus saving time and cutting costs.

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