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Understanding the Synergy Between Artificial Intelligence & Data Science

Pickl AI

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. Machine Learning Machine Learning (ML) is a crucial component of Data Science.

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Creating an artificial intelligence 101

Dataconomy

How to create an artificial intelligence? The creation of artificial intelligence (AI) has long been a dream of scientists, engineers, and innovators. Understanding artificial intelligence Before diving into the process of creating AI, it is important to understand the key concepts and types of AI.

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#39 Top 5 ML Algorithms, Graph RAG, & Tutorial for Creating an Agentic Multimodal Chatbot.

Towards AI

Featured Community post from the Discord Aman_kumawat_41063 has created a GitHub repository for applying some basic ML algorithms. It offers pure NumPy implementations of fundamental machine learning algorithms for classification, clustering, preprocessing, and regression. This repo is designed for educational exploration.

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Who By Prior: A Machine Learning Song

Mlearning.ai

I think I managed to get most of the ML players in there…?? AI-generated image ( craiyon ) [link] Who By Prior And who by prior, who by Bayesian Who in the pipeline, who in the cloud again Who by high dimension, who by decision tree Who in your many-many weights of net Who by very slow convergence And who shall I say is boosting?

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Machine learning world easy-to-understand overview for beginners

Mlearning.ai

Basically, Machine learning is a part of the Artificial intelligence field, which is mainly defined as a technic that gives the possibility to predict the future based on a massive amount of past known or unknown data. ML algorithms can be broadly divided into supervised learning , unsupervised learning , and reinforcement learning.

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Exploring the dynamic fusion of AI and the IoT

Dataconomy

The integration of artificial intelligence in Internet of Things introduces new dimensions of efficiency, automation, and intelligence to our daily lives. Simultaneously, artificial intelligence has revolutionized the way machines learn, reason, and make decisions.

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Supervised learning vs Unsupervised learning

Pickl AI

Apparently, ML algorithms ensure to train of the data enabling the new data input to make compelling predictions and deliver accurate results. Accordingly, Examples of Supervised learning include linear regression, logistic regression , decision trees, random forests and neural networks.