Pickl AI

JULY 12, 2024

Machine Learning algorithms are trained on large amounts of data, and they can then use that data to make predictions or decisions about new data. There are three main types of Machine Learning: supervised learning, unsupervised learning, and reinforcement learning.

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How to Learn Machine Learning

MAY 14, 2023

Acquiring Essential Machine Learning Knowledge Once you have a strong foundation in mathematics and programming, it’s time to dive into the world of machine learning. Additionally, you should familiarize yourself with essential machine learning concepts such as feature engineering, model evaluation, and hyperparameter tuning.

Machine Learning 52

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ODSC - Open Data Science

SEPTEMBER 19, 2023

Depending on the position, and company, it can require a strong understanding of natural language processing, computer science, linguistics, and software engineering. Learn from some of the leading minds who are pioneering the latest advancements in large language models.

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Snorkel AI

MARCH 1, 2023

Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy.

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Pickl AI

AUGUST 1, 2024

Unlike traditional Machine Learning, which often relies on feature extraction and simpler models, Deep Learning utilises multi-layered neural networks to automatically learn features from raw data. Data Quality and Quantity Deep Learning models require large amounts of high-quality, labelled training data to learn effectively.

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IBM Journey to AI blog

JULY 6, 2023

These computer science terms are often used interchangeably, but what differences make each a unique technology? To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. Computer vision is a factor in the development of self-driving cars.

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Pickl AI

SEPTEMBER 18, 2024

Typical Work Environments and Industries Machine Learning Engineers often work in various settings, including tech companies, financial institutions, healthcare organisations, and research institutions. Tech companies, they might focus on developing recommendation systems, fraud detection algorithms, or Natural Language Processing tools.

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Pickl AI

JULY 10, 2024

Inspired by the human brain, neural networks are crucial for deep learning, a subset of ML that deals with large, complex datasets. Natural Language Processing (NLP) allows machines to understand and generate human language, enhancing interactions between humans and machines. Focus on career-essential soft skills.

Machine Learning 52

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Dataconomy

MARCH 13, 2023

With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. However, the process of creating AI can seem daunting to those who are unfamiliar with the technicalities involved. What is required to build an AI system?

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AWS Machine Learning Blog

OCTOBER 30, 2024

Sentence transformers are powerful deep learning models that convert sentences into high-quality, fixed-length embeddings, capturing their semantic meaning. These embeddings are useful for various natural language processing (NLP) tasks such as text classification, clustering, semantic search, and information retrieval.

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IBM Journey to AI blog

JULY 6, 2023

That’s where data science comes in. The term data science was first used in the 1960s when it was interchangeable with the phrase “computer science.” ” “Data science” was first used as an independent discipline in 2001.

Machine Learning 80

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Pickl AI

SEPTEMBER 12, 2024

Artificial Intelligence (AI): A branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. Association Rule Learning: A rule-based Machine Learning method to discover interesting relationships between variables in large databases.

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Becoming Human

MARCH 16, 2023

Like in the human brain, these neurons work together to process information and make predictions or decisions. The more layers of interconnected neurons a neural network has, the more “deep” it is.

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Applied Data Science

MARCH 11, 2022

Our internal agents are playing games until they learn how to cooperate and trick us into believing we are an individual. Here, we are interested in the formal definition born in economics and used in computer science: In a game, two or more agents, are interacting by performing actions, which give them rewards.

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Hacker News

MARCH 25, 2022

Transformers made self-supervised learning possible, and AI jumped to warp speed,” said NVIDIA founder and CEO Jensen Huang in his keynote address this week at GTC. Transformers are in many cases replacing convolutional and recurrent neural networks (CNNs and RNNs), the most popular types of deep learning models just five years ago.

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ODSC - Open Data Science

FEBRUARY 14, 2023

ChatGPT is a next-generation language model (referred to as GPT-3.5) Some examples of large language models include GPT (Generative Pre-training Transformer), BERT (Bidirectional Encoder Representations from Transformers), and RoBERTa (Robustly Optimized BERT Approach). But users may find ways to bypass safeguards.

Database 124

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Pickl AI

SEPTEMBER 23, 2024

Understanding Data Science Data Science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. It combines principles from statistics, mathematics, computer science, and domain-specific knowledge to analyse and interpret complex data.

Artificial Intelligence 52

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Pickl AI

APRIL 2, 2024

Data science is the process of extracting the valuable minerals – the insights – that can transform your business. It’s a blend of statistics, computer science, and domain knowledge used to extract knowledge and create solutions from data. Data science for business leaders isn’t about becoming a coding pro.

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AWS Machine Learning Blog

AUGUST 7, 2023

AWS received about 100 samples of labeled data from the customer, which is a lot less than the 1,000 samples recommended for fine-tuning an LLM in the data science community. A rigorous and effective NLP solution, if provided sufficient amounts of labeled data, would be to train a custom language model using the customer’s labeled data.

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