Data Science Dojo

JUNE 11, 2024

These include image recognition, natural language processing, autonomous vehicles, financial services, healthcare, recommender systems, gaming and entertainment, and speech recognition. Inspired by human brain structure, they are designed to perform as powerful tools for pattern recognition, classification, and prediction tasks.

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Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. Image captioning integrates computer vision, which interprets visual information, and NLP, which produces human language.

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Dataconomy

AUGUST 31, 2023

The classification model learns from the training data, identifying the distinguishing characteristics between each class, enabling it to make informed predictions. Classification in machine learning can be a versatile tool with numerous applications across various industries.

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Data Science Dojo

AUGUST 19, 2024

These professionals venture into new frontiers like machine learning, natural language processing, and computer vision, continually pushing the limits of AI’s potential. Supervised learning: This involves training a model on a labeled dataset, where each data point has a corresponding output or target variable.

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Dataconomy

APRIL 18, 2023

Understanding the basics of artificial intelligence Artificial intelligence is an interdisciplinary field of study that involves creating intelligent machines that can perform tasks that typically require human-like cognitive abilities such as learning, reasoning, and problem-solving.

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Dataversity

DECEMBER 16, 2022

2022 was a big year for AI, and we’ve seen significant advancements in various areas – including natural language processing (NLP), machine learning (ML), and deep learning. Unsupervised and self-supervised learning are making ML more accessible by lowering the training data requirements.

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Hacker News

MAY 3, 2023

The core process is a general technique known as self-supervised learning , a learning paradigm that leverages the inherent structure of the data itself to generate labels for training. Fine-tuning may involve further training the pre-trained model on a smaller, task-specific labeled dataset, using supervised learning.

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AWS Machine Learning Blog

JULY 18, 2023

It’s important to take extra precautions to protect your device and sensitive information. As technology is improving, the detection of spam emails becomes a challenging task due to its changing nature. Text classification is essential for applications like web searches, information retrieval, ranking, and document classification.

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Towards AI

JULY 23, 2023

In the first part of the series, we talked about how Transformer ended the sequence-to-sequence modeling era of Natural Language Processing and understanding. Semi-Supervised Sequence Learning As we all know, supervised learning has a drawback, as it requires a huge labeled dataset to train.

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Towards AI

FEBRUARY 20, 2024

Types of Machine Learning There are three main categories of Machine Learning, Supervised learning, Unsupervised learning, and Reinforcement learning. Supervised learning: This involves learning from labeled data, where each data point has a known outcome. Models […]

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Dataconomy

MARCH 14, 2023

In recent years, natural language processing and conversational AI have gained significant attention as technologies that are transforming the way we interact with machines and each other. Moreover, the model training process is capable of adapting to new languages and data effectively.

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Towards AI

JANUARY 30, 2024

GPT4, Stable Diffusion, Llama, BERT, Gemini Large Language Models (LLMs) Foundation models, trained on the “Transformer Architecture”, that can perform a wide array of Natural Language Processing (NLP) tasks like text generation, classification, summarisation etc. LLMs don’t claim to reproduce accurate information.

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Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans. By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions.

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Pickl AI

NOVEMBER 13, 2024

The answer lies in the various types of Machine Learning, each with its unique approach and application. In this blog, we will explore the four primary types of Machine Learning: Supervised Learning, UnSupervised Learning, semi-Supervised Learning, and Reinforcement Learning.

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Becoming Human

MAY 11, 2023

Empowering Startups and Entrepreneurs | InvestBegin.com | investbegin The success of ChatGPT can be attributed to several key factors, including advancements in machine learning, natural language processing, and big data. NLP is a field of AI that focuses on enabling computers to understand and process human language.

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Dataconomy

APRIL 3, 2023

ML models are designed to learn from data and make predictions or decisions based on that data. Types of ML There are three main types of machine learning: Supervised learning: In supervised learning, the algorithm is trained on labeled data.

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Dataconomy

APRIL 3, 2023

ML models are designed to learn from data and make predictions or decisions based on that data. Types of ML There are three main types of machine learning: Supervised learning: In supervised learning, the algorithm is trained on labeled data.

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Data Science Dojo

JULY 4, 2024

User Satisfaction : For example, in natural language processing applications like chatbots, RLHF helps generate responses that are more engaging and satisfying to users by sounding more natural and providing appropriate contextual information.

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Explosion

MAY 17, 2023

A lot of people are building truly new things with Large Language Models (LLMs), like wild interactive fiction experiences that weren’t possible before. But if you’re working on the same sort of Natural Language Processing (NLP) problems that businesses have been trying to solve for a long time, what’s the best way to use them?

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ODSC - Open Data Science

AUGUST 29, 2023

Natural Language Processing Engineer Natural Language Processing Engineers who specialize in prompt engineering are linguistic architects when it comes to AI communication. As AI models become more sophisticated and versatile, the demand for tailored, context-aware interactions grows.

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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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Becoming Human

MAY 9, 2024

Artificial intelligence, machine learning, natural language processing, and other related technologies are paving the way for a smarter “everything.” NLP in finance includes semantic analysis, information extraction, and text analysis. How Does Data Labeling Work in Finance?

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Pickl AI

OCTOBER 21, 2024

Summary: Zero-Shot Learning (ZSL) empowers AI systems to recognize and classify new categories without needing labelled examples. By leveraging auxiliary information such as semantic attributes, ZSL enhances scalability, reduces data dependency, and improves generalisation. Poorly defined attributes may lead to inaccurate predictions.

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Mlearning.ai

AUGUST 4, 2023

Fine-tuning large language models (LLMs) has become a powerful technique for achieving impressive performance in various natural language processing tasks. Achieving higher performance is often challenging, as the context window restricts the model’s ability to process long sequences of information effectively.

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Pickl AI

NOVEMBER 24, 2024

Each layer captures essential features while discarding irrelevant information. It contains the most crucial information from the input data in a significantly reduced form. Can I Use Autoencoders for Supervised Learning Tasks? Yes, autoencoders can enhance supervised learning tasks.

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Dataconomy

SEPTEMBER 13, 2023

As a result, diffusion models have become a popular tool in many fields of artificial intelligence, including computer vision, natural language processing, and audio synthesis. Diffusion models have numerous applications in computer vision, natural language processing, and audio synthesis.

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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. ANNs are made up of interconnected nodes, or “neurons,” that are connected by pathways, called “synapses.” The more layers of interconnected neurons a neural network has, the more “deep” it is.

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Pickl AI

AUGUST 14, 2024

They consist of interconnected nodes that learn complex patterns in data. Different types of neural networks, such as feedforward, convolutional, and recurrent networks, are designed for specific tasks like image recognition, Natural Language Processing, and sequence modelling.

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Women in Big Data

DECEMBER 13, 2023

The Bay Area Chapter of Women in Big Data (WiBD) hosted its second successful episode on the NLP (Natural Language Processing), Tools, Technologies and Career opportunities. Natural Language Processing (NLP) is a branch of Artificial Intelligence (AI) that helps computers understand, interpret and manipulate human language.

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AWS Machine Learning Blog

MAY 8, 2024

This supervised learning algorithm supports transfer learning for all pre-trained models available on Hugging Face. We also provided the functionality to use any Hugging Face fill-mask or text classification model for inference and transfer learning. For more information, check out the example notebook.

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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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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.

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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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Data Science 101

OCTOBER 31, 2019

A definition from the book ‘Data Mining: Practical Machine Learning Tools and Techniques’, written by, Ian Witten and Eibe Frank describes Data mining as follows: “ Data mining is the extraction of implicit, previously unknown, and potentially useful information from data. Classification. Regression.

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Pickl AI

SEPTEMBER 16, 2024

This section will explore the top 10 Machine Learning algorithms that you should know in 2024. Linear Regression Linear regression is one of the simplest and most widely used algorithms in Machine Learning. It is a supervised learning algorithm that predicts a continuous target variable based on one or more predictor variables.

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Dataconomy

MARCH 27, 2023

Some of the ways in which ML can be used in process automation include the following: Predictive analytics:  ML algorithms can be used to predict future outcomes based on historical data, enabling organizations to make better decisions. Technology: Includes a range of technologies, including ML and deep learning.

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Dataconomy

APRIL 4, 2023

Reminder : Training data refers to the data used to train an AI model, and commonly there are three techniques for it: Supervised learning: The AI model learns from labeled data, which means that each data point has a known output or target value. The information from previous decisions is analyzed via the decision tree.

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