Data Science Dojo

FEBRUARY 15, 2023

Tech-Vidvan ’s “Top 10”: Linear Regression Logistic Regression Decision Trees Naive Bayes K-Nearest Neighbors Support Vector Machine K-Means Clustering Principal Component Analysis Neural Networks Random Forests P.

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K-nearest Neighbors Decision Trees Support Vector Machines Algorithm 195

IBM Journey to AI blog

DECEMBER 20, 2023

And retailers frequently leverage data from chatbots and virtual assistants, in concert with ML and natural language processing (NLP) technology, to automate users’ shopping experiences. Supervised machine learning Supervised machine learning is a type of machine learning where the model is trained on a labeled dataset (i.e.,

Machine Learning 77

Machine Learning Machine Learning Supervised Learning Clustering 77

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.

Machine Learning 67

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 67

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. Here is a brief description of the same.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Dataconomy

MAY 25, 2023

Here are some ways AI enhances IoT devices: Advanced data analysis AI algorithms can process and analyze vast volumes of IoT-generated data. By leveraging techniques like machine learning and deep learning, IoT devices can identify trends, anomalies, and patterns within the data.

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Internet of Things Artificial Intelligence Artificial Intelligence AI 160

IBM Journey to AI blog

JULY 6, 2023

Machine learning can then “learn” from the data to create insights that improve performance or inform predictions. Just as humans can learn through experience rather than merely following instructions, machines can learn by applying tools to data analysis.

Machine Learning 56

Machine Learning Machine Learning Data Science Big Data 56