Data Analysis, Supervised Learning and Support Vector Machines

Data Analysis

Supervised Learning

Support Vector Machines

Problem-solving tools offered by digital technology

Data Science Dojo

FEBRUARY 15, 2023

Zheng’s “Guide to Data Structures and Algorithms” Parts 1 and Part 2 1) Big O Notation 2) Search 3) Sort 3)–i)–Quicksort 3)–ii–Mergesort 4) Stack 5) Queue 6) Array 7) Hash Table 8) Graph 9) Tree (e.g.,

K-nearest Neighbors

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Five machine learning types to know

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

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

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

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Exploring the dynamic fusion of AI and the IoT

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.

Internet of Things

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Unleashing the Power of Applied Text Mining in Python: Revolutionize Your Data Analysis

Pickl AI

AUGUST 1, 2023

It is widely used in various applications such as spam detection, sentiment analysis, news categorization, and customer feedback classification. Machine Learning algorithms, including Naive Bayes, Support Vector Machines (SVM), and deep learning models, are commonly used for text classification.

Data Analysis

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Artificial Intelligence Using Python: A Comprehensive Guide

Pickl AI

JULY 12, 2024

Scikit-learn: A simple and efficient tool for data mining and data analysis, particularly for building and evaluating machine learning models. TensorFlow and Keras: TensorFlow is an open-source platform for machine learning. classification, regression) and data characteristics.

Artificial Intelligence

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Understand The Difference Between Machine Learning and Deep Learning

Pickl AI

FEBRUARY 7, 2025

Features : The attributes or characteristics of the data used to make predictions. Types of Machine Learning Machine Learning is divided into three main types based on how the algorithm learns from the data: Supervised Learning In supervised learning , the algorithm is trained on labelled data.

Deep Learning

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Understanding and Building Machine Learning Models

Pickl AI

NOVEMBER 18, 2024

The main types are supervised, unsupervised, and reinforcement learning, each with its techniques and applications. Supervised Learning In Supervised Learning , the algorithm learns from labelled data, where the input data is paired with the correct output. predicting house prices).

Machine Learning

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Data science vs. machine learning: What’s the difference?

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

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Must-Have Skills for a Machine Learning Engineer

Pickl AI

NOVEMBER 28, 2024

These techniques span different types of learning and provide powerful tools to solve complex real-world problems. Supervised Learning Supervised learning is one of the most common types of Machine Learning, where the algorithm is trained using labelled data.

Machine Learning

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Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

SEPTEMBER 12, 2024

Data Cleaning: Raw data often contains errors, inconsistencies, and missing values. Data cleaning identifies and addresses these issues to ensure data quality and integrity. Data Visualisation: Effective communication of insights is crucial in Data Science.

Data Analyst

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The Age of BioInformatics: Part 2

Heartbeat

OCTOBER 25, 2023

The field demands a unique combination of computational skills and biological knowledge, making it a perfect match for individuals with a data science and machine learning background.

Machine Learning

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Understanding the Synergy Between Artificial Intelligence & Data Science

Pickl AI

SEPTEMBER 23, 2024

Summary: The blog explores the synergy between Artificial Intelligence (AI) and Data Science, highlighting their complementary roles in Data Analysis and intelligent decision-making. Introduction Artificial Intelligence (AI) and Data Science are revolutionising how we analyse data, make decisions, and solve complex problems.

Artificial Intelligence

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Credit Card Fraud Detection Using Spectral Clustering

PyImageSearch

SEPTEMBER 16, 2024

Anomaly detection ( Figure 2 ) is a critical technique in data analysis used to identify data points, events, or observations that deviate significantly from the norm. Machine Learning Methods Machine learning methods ( Figure 7 ) can be divided into supervised, unsupervised, and semi-supervised learning techniques.

Clustering

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Data Science Current

Problem-solving tools offered by digital technology

Five machine learning types to know

Webinars

Trending Sources

Anomaly detection in machine learning: Finding outliers for optimization of business functions

Webinars

Exploring the dynamic fusion of AI and the IoT

Unleashing the Power of Applied Text Mining in Python: Revolutionize Your Data Analysis

Top 10 Data Science Interviews Questions and Expert Answers

Artificial Intelligence Using Python: A Comprehensive Guide

Understand The Difference Between Machine Learning and Deep Learning

Understanding and Building Machine Learning Models

Data science vs. machine learning: What’s the difference?

Must-Have Skills for a Machine Learning Engineer

Basic Data Science Terms Every Data Analyst Should Know

The Age of BioInformatics: Part 2

Understanding the Synergy Between Artificial Intelligence & Data Science

Credit Card Fraud Detection Using Spectral Clustering

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