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. Its divided into foundational mathematics, practical implementation, and exploring neural networks’ inner workings.

Artificial Intelligence 52

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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. They work on complex problems that require advanced neural networks to analyse vast amounts of data. Hyperparameter Tuning: Adjusting model parameters to improve performance and accuracy.

Deep Learning 52

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Ofemwire

MARCH 1, 2024

It’s like a robot that plays a game but doesn’t learn from its mistakes. Limited Memory AI : These AIs can remember some things from the past to help them make decisions in the present. It’s like a robot that remembers where it’s been before so it can figure out where to go next.

Neural Network 52

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Pickl AI

SEPTEMBER 17, 2024

Machine Learning (ML) is a subset of AI that focuses on developing algorithms and statistical models that enable systems to perform specific tasks effectively without being explicitly programmed. Explain The Concept of Supervised and Unsupervised Learning. What Is the Purpose of The Activation Function in Artificial Neural Networks?

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Neural Network Machine Learning 52

Pickl AI

JULY 24, 2024

The Golden Age of AI (1960s-1970s) Experts often refer to the 1960s and 1970s as the “Golden Age of AI.” ” During this time, researchers made remarkable strides in natural language processing, robotics, and expert systems. In 2011, IBM’s Watson gained fame by winning the quiz show “Jeopardy!

Artificial Intelligence 52

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Pickl AI

JANUARY 29, 2024

AI comprises Natural Language Processing, computer vision, and robotics. ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition. AI Engineer, Machine Learning Engineer, and Robotics Engineer are prominent roles in AI.

Data Science 52

Data Science ML Machine Learning Artificial Intelligence 52

Viso.ai

DECEMBER 6, 2023

State of Computer Vision Tasks in 2024 The field of computer vision today involves advanced AI algorithms and architectures, such as convolutional neural networks (CNNs) and vision transformers ( ViTs ), to process, analyze, and extract relevant patterns from visual data. Get a demo here.

Computer Vision 52

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ODSC - Open Data Science

FEBRUARY 25, 2025

This track brings together industry pioneers and leading researchers to showcase the breakthroughs shaping tomorrows AI landscape. Deep Learning & Multi-Modal Models TrackPush Neural NetworksFurther Dive into the latest advancements in neural networks, multimodal learning, and self-supervised models.

Data Scientist 52

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Pickl AI

NOVEMBER 5, 2024

AI encompasses various subfields, including Machine Learning (ML), Natural Language Processing (NLP), robotics, and computer vision. Together, Data Science and AI enable organisations to analyse vast amounts of data efficiently and make informed decisions based on predictive analytics.

Data Science 52

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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. These methods create detailed 3D maps of environments.

Computer Vision 52

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Pickl AI

NOVEMBER 18, 2024

It’s commonly used in robotics, gaming, and autonomous systems. 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.

Machine Learning 52

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IBM Journey to AI blog

SEPTEMBER 3, 2024

According to a World Economic Forum report, nearly half of the surveyed organizations expect AI to create new jobs, while almost a quarter see it as a cause of job losses. Take action: Adopt explainable AI techniques. Explore explainable AI tools, such as IBM’s open source AI Explainability 360 toolkit.

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