Heartbeat

OCTOBER 11, 2023

This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. Supervised, unsupervised, and reinforcement learning : Machine learning can be categorized into different types based on the learning approach.

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Pickl AI

AUGUST 1, 2023

Types of Machine Learning Model: Machine Learning models can be broadly categorized as: 1. Supervised Learning Models Supervised learning involves training a model on labelled data, where the input features and corresponding target outputs are provided.

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IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

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Dataconomy

OCTOBER 5, 2023

AI practitioners choose an appropriate machine learning model or algorithm that aligns with the problem at hand. Common choices include neural networks (used in deep learning), decision trees, support vector machines, and more. With the model selected, the initialization of parameters takes place.

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Pickl AI

FEBRUARY 12, 2024

Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks.

Data Science 52

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Pickl AI

AUGUST 1, 2023

Machine Learning algorithms, including Naive Bayes, Support Vector Machines (SVM), and deep learning models, are commonly used for text classification. Gather a dataset of customer support tickets with different categories, such as billing, technical issues, or product inquiries.

Data Analysis 52

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Dataconomy

MAY 25, 2023

By leveraging techniques like machine learning and deep learning, IoT devices can identify trends, anomalies, and patterns within the data. Here are some important machine learning techniques used in IoT: Supervised learning Supervised learning involves training machine learning models with labeled datasets.

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