Towards AI

JUNE 19, 2024

Deciding What Algorithm to Use for Earth Observation. Picking the best algorithm is usually tricky or even frustrating. Especially if you do not know what you are looking for, you might utilize an algorithm and get an undesirable outcome, which in turn will take you back to square one. How to determine the right algorithm 1.

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Algorithm Clustering Support Vector Machines Machine Learning 81

Data Science Dojo

JULY 23, 2024

With the growing use of machine learning (ML) models to handle, store, and manage data, the efficiency and impact of enterprises have also increased. Categorical data is one such form of information that is handled by ML models using different methods. This conversion allows models to process the data and extract valuable information.

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Pickl AI

AUGUST 8, 2024

Summary: Support Vector Machine (SVM) is a supervised Machine Learning algorithm used for classification and regression tasks. Introduction Machine Learning has revolutionised various industries by enabling systems to learn from data and make informed decisions.

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Machine Learning Machine Learning Support Vector Machines Algorithm 52

Data Science Dojo

APRIL 10, 2023

Data mining can help governments identify areas of concern, allocate resources, and make informed policy decisions. Selecting the right algorithm There are several data mining algorithms available, each with its strengths and weaknesses. Choose the appropriate technique based on your dataset and analysis needs.

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Dataconomy

AUGUST 25, 2023

Machine learning, computer vision, and signal processing techniques have been extensively explored to address this problem by leveraging information from various multimedia data sources. Fundamental frequency is related to voice pitch and can provide information about emotional state.

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Towards AI

APRIL 5, 2023

The articles cover a range of topics, from the basics of Rust to more advanced machine learning concepts, and provide practical examples to help readers get started with implementing ML algorithms in Rust. Rust has several libraries and frameworks for machine learning, lets talk about a few of them!

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Dataconomy

MAY 25, 2023

On the other hand, artificial intelligence is the simulation of human intelligence in machines that are programmed to think and learn like humans. By leveraging advanced algorithms and machine learning techniques, IoT devices can analyze and interpret data in real-time, enabling them to make informed decisions and take autonomous actions.

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Pickl AI

SEPTEMBER 16, 2024

Summary: This blog highlights ten crucial Machine Learning algorithms to know in 2024, including linear regression, decision trees, and reinforcement learning. Each algorithm is explained with its applications, strengths, and weaknesses, providing valuable insights for practitioners and enthusiasts in the field.

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Machine Learning Machine Learning Algorithm Decision Trees 52

Dataconomy

AUGUST 31, 2023

The classification model learns from the training data, identifying the distinguishing characteristics between each class, enabling it to make informed predictions. Classification in machine learning can be a versatile tool with numerous applications across various industries. Next, you need to select a model.

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Towards AI

FEBRUARY 20, 2024

Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms. You might be using machine learning algorithms from everything you see on OTT or everything you shop online.

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Towards AI

APRIL 14, 2023

In the second part, I will present and explain the four main categories of XML algorithms along with some of their limitations. However, typical algorithms do not produce a binary result but instead, provide a relevancy score for which labels are the most appropriate. Thus tail labels have an inflated score in the metric.

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Dataconomy

OCTOBER 5, 2023

Data preprocessing tasks can include data cleaning to remove errors or inconsistencies, normalization to bring data within a consistent range, and feature engineering to extract meaningful information from raw data. AI practitioners choose an appropriate machine learning model or algorithm that aligns with the problem at hand.

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Dataconomy

JUNE 13, 2023

In this era of information overload, utilizing the power of data and technology has become paramount to drive effective decision-making. Decision intelligence is not just about crunching numbers or relying on algorithms; it is about unlocking the true potential of data to make smarter choices and fuel business success.

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Towards AI

APRIL 11, 2023

Feature Extraction Feature Extraction is basically extracting relevant information from the pre-processed image that can be used for classification. Classification In Classification, we use an ML Algorithm to classify the digit based on its features. Support Vector Machines (SVMs) are another ML models that can be used for HDR.

Machine Learning 98

Machine Learning Machine Learning Support Vector Machines Decision Trees 98

Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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Becoming Human

MARCH 16, 2023

AI began back in the 1950s as a simple series of “if, then rules” and made its way into healthcare two decades later after more complex algorithms were developed. Machine Learning Machine learning (ML) focuses on training computer algorithms to learn from data and improve their performance, without being explicitly programmed.

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IBM Journey to AI blog

DECEMBER 19, 2023

This type of machine learning is useful in known outlier detection but is not capable of discovering unknown anomalies or predicting future issues. Local outlier factor (LOF ): Local outlier factor is similar to KNN in that it is a density-based algorithm.

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Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Dataconomy

AUGUST 9, 2023

This is where the power of machine learning (ML) comes into play. Machine learning algorithms, with their ability to recognize patterns, anomalies, and trends within vast datasets, are revolutionizing network traffic analysis by providing more accurate insights, faster response times, and enhanced security measures.

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Towards AI

JULY 20, 2023

As the capabilities of high-powered computers and ML algorithms have grown, so have opportunities to improve the SLR process. New research has also begun looking at deep learning algorithms for automatic systematic reviews, According to van Dinter et al. This study by Bui et al.

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Natural Language Processing ML ML Support Vector Machines 98

Heartbeat

MARCH 8, 2023

Text Categorization Text categorization is a machine-learning approach that divides the text into specific categories based on its content. The goal is to automatically classify documents based on the textual information contained within them. Data mining, text classification, and information retrieval are just a few applications.

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Machine Learning Machine Learning Algorithm Data Mining 52

Mlearning.ai

FEBRUARY 2, 2023

The Multi-Armed Bandit (MAB) algorithm is a type of reinforcement learning algorithm that addresses the trade-off between exploration and exploitation in decision-making. The name “Multi-Armed Bandit” is inspired by a classic gambling problem in which a gambler has to decide which of several slot machines, or “arms,” to play.

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K-nearest Neighbors Support Vector Machines Algorithm Decision Trees 52

Mlearning.ai

MAY 20, 2023

image from lexica.art Machine learning algorithms can be used to capture gender detection from sound by learning patterns and features in the audio data that are indicative of gender differences. Data Collection: A dataset of audio samples with labeled gender information is collected.

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines Cross Validation 52

Pickl AI

AUGUST 1, 2023

Text mining is primarily a technique in the field of Data Science that encompasses the extraction of meaningful insights and information from unstructured textual data. This helps businesses gain insights into market trends, consumer preferences, and competitive landscapes, allowing them to make informed strategic decisions.

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Data Analysis Data Analysis Python Support Vector Machines 52

Pickl AI

AUGUST 1, 2023

In this blog, we will delve into the fundamental concepts of data model for Machine Learning, exploring their types. What is Machine Learning? Examples of supervised learning models include linear regression, decision trees, support vector machines, and neural networks.

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines Decision Trees 52

Data Science Blog

OCTOBER 20, 2024

Data-Driven Decision Making: Attribution models empower marketers to make informed, data-driven decisions, leading to more effective campaign strategies and better alignment between marketing and sales efforts. For more information on how to calculate the marginal distribution, see Zhao et al.

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Dataconomy

MARCH 13, 2023

Algorithms:  AI algorithms are used to process the data and extract insights from it. There are several types of AI algorithms, including supervised learning, unsupervised learning, and reinforcement learning. Develop AI models using machine learning or deep learning algorithms.

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Mlearning.ai

FEBRUARY 17, 2023

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.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

DagsHub

JUNE 3, 2024

By creating a new feature called “body mass index” (BMI), which combines height and weight in a specific formula, you can provide a more informative representation of the model. For example, this could be the weather based on past weather information or a particular stock's price.

Machine Learning 52

Machine Learning Machine Learning Decision Trees ML 52

Pickl AI

JULY 31, 2023

Examples of Eager Learning Algorithms: Logistic Regression : A classic Eager Learning algorithm used for binary classification tasks. Support Vector Machines (SVM) : SVM is a powerful Eager Learning algorithm used for both classification and regression tasks. Eager Learning Algorithms: How does it work?

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Pickl AI

FEBRUARY 12, 2024

Technical Proficiency Data Science interviews typically evaluate candidates on a myriad of technical skills spanning programming languages, statistical analysis, Machine Learning algorithms, and data manipulation techniques. Differentiate between supervised and unsupervised learning algorithms.

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Heartbeat

APRIL 17, 2023

Photo by Shahadat Rahman on Unsplash Introduction Machine learning (ML) focuses on developing algorithms and models that can learn from data and make predictions or decisions. One of the goals of ML is to enable computers to process and analyze data in a way that is similar to how humans process information. synonyms).

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Natural Language Processing Support Vector Machines Machine Learning Machine Learning 52

PyImageSearch

NOVEMBER 13, 2023

One of the most popular deep learning-based object detection algorithms is the family of R-CNN algorithms, originally introduced by Girshick et al. Since then, the R-CNN algorithm has gone through numerous iterations, improving the algorithm with each new publication and outperforming traditional object detection algorithms (e.g.,

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Pickl AI

JANUARY 29, 2024

Summary: In the tech landscape of 2024, the distinctions between Data Science and Machine Learning are pivotal. Data Science extracts insights, while Machine Learning focuses on self-learning algorithms. Markets for each field are booming, offering diverse job roles, especially in Machine Learning for Data Analytics.

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Dataconomy

APRIL 4, 2023

Artificial Intelligence (AI) models are the building blocks of modern machine learning algorithms that enable machines to learn and perform complex tasks. The information from previous decisions is analyzed via the decision tree. This technique is based on the concept that related information tends to cluster together.

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K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Artificial Intelligence (AI) models are the building blocks of modern machine learning algorithms that enable machines to learn and perform complex tasks. The information from previous decisions is analyzed via the decision tree. This technique is based on the concept that related information tends to cluster together.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

AWS Machine Learning Blog

FEBRUARY 5, 2024

In this post, we present one approach for zoonotic disease prevention that uses Amazon SageMaker geospatial capabilities to create a tool that provides more accurate disease spread information to health scientists to help them save more lives, quicker. Zoonotic diseases affect both animals and humans.

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ML ML AWS Analytics 121

Heartbeat

AUGUST 1, 2023

A World of Computer Vision Outside of Deep Learning Photo by Museums Victoria on Unsplash IBM defines computer vision as “a field of artificial intelligence (AI) that enables computers and systems to derive meaningful information from digital images, videos and other visual inputs [1].” It detects corners.

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