Remove Azure Remove Data Preparation Remove Natural Language Processing
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6 AI tools revolutionizing data analysis: Unleashing the best in business

Data Science Dojo

TensorFlow First on the AI tool list, we have TensorFlow which is an open-source software library for numerical computation using data flow graphs. It is used for machine learning, natural language processing, and computer vision tasks. RapidMiner was also used by the World Bank to develop a poverty index.

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Your Complete Roadmap to Become an Azure Data Scientist

Pickl AI

Summary: This blog provides a comprehensive roadmap for aspiring Azure Data Scientists, outlining the essential skills, certifications, and steps to build a successful career in Data Science using Microsoft Azure. What is Azure?

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Top 10 Deep Learning Platforms in 2024

DagsHub

Libraries and Extensions: Includes torchvision for image processing, touchaudio for audio processing, and torchtext for NLP. Notable Use Cases PyTorch is extensively used in natural language processing (NLP), including applications like sentiment analysis, machine translation, and text generation.

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AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs

IBM Journey to AI blog

Primary activities AIOps relies on big data-driven analytics , ML algorithms and other AI-driven techniques to continuously track and analyze ITOps data. The process includes activities such as anomaly detection, event correlation, predictive analytics, automated root cause analysis and natural language processing (NLP).

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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

Neural networks are inspired by the structure of the human brain, and they are able to learn complex patterns in data. Deep Learning has been used to achieve state-of-the-art results in a variety of tasks, including image recognition, Natural Language Processing, and speech recognition.

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Large Language Models: A Complete Guide

Heartbeat

LLMs are one of the most exciting advancements in natural language processing (NLP). We will explore how to better understand the data that these models are trained on, and how to evaluate and optimize them for real-world use. LLMs rely on vast amounts of text data to learn patterns and generate coherent text.

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AI Models as a Service (AIMaaS): A Detailed Overview

Pickl AI

The process typically involves several key steps: Model Selection: Users choose from a library of pre-trained models tailored for specific applications such as Natural Language Processing (NLP), image recognition, or predictive analytics. Predictive Analytics : Models that forecast future events based on historical data.

AI 52