Towards AI

JUNE 19, 2024

– Algorithms: Support Vector Machines (SVM), Random Forest, Neural Networks. – Algorithms: K-means Clustering, ISODATA. Use Cases: Initial data exploration, finding natural clusters in data. With the right guidance, selecting the most suitable algorithm will become straightforward and efficient.

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Algorithm Clustering Support Vector Machines Machine Learning 81

IBM Journey to AI blog

DECEMBER 20, 2023

Supervised learning is commonly used for risk assessment, image recognition, predictive analytics and fraud detection, and comprises several types of algorithms. Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others. temperature, salary).

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

AWS Machine Learning Blog

JANUARY 17, 2024

We can analyze activities by identifying stops made by the user or mobile device by clustering pings using ML models in Amazon SageMaker. A cluster of pings represents popular spots where devices gathered or stopped, such as stores or restaurants. Manually managing a DIY compute cluster is slow and expensive.

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Clustering AWS ML ML 134

Dataconomy

JUNE 13, 2023

Statistical methods, machine learning algorithms, and data mining techniques are employed to extract meaningful insights from the collected data. This analysis may involve feature engineering, dimensionality reduction, clustering, classification, regression, or other statistical modeling approaches.

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Power BI Data Analysis Data Analysis Artificial Intelligence 103

Dataconomy

MAY 25, 2023

When AI and IoT converge, we witness a synergy where AI empowers IoT devices with advanced analytics, automation, and intelligent decision-making. AI algorithms can uncover hidden correlations within IoT data, enabling predictive analytics and proactive actions.

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Internet of Things Artificial Intelligence Artificial Intelligence AI 160

Pickl AI

AUGUST 1, 2023

Text mining is also known as text analytics or Natural Language Processing (NLP). 7 Advantages of Text Mining Text mining, also known as text analytics, refers to the process of extracting useful information and insights from large volumes of unstructured text data. within the text.

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Data Analysis Data Analysis Python Support Vector Machines 52

Dataconomy

AUGUST 9, 2023

It constructs multiple decision trees and combines their predictions to achieve accurate results in identifying different types of network traffic Support Vector Machines (SVM) : SVM is used for both classification and anomaly detection.

Machine Learning 91

Machine Learning Machine Learning ML ML 91

Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? Let’s dig deeper and learn more about them!

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K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? Let’s dig deeper and learn more about them!

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K-nearest Neighbors Decision Trees AI AI 91

Pickl AI

AUGUST 9, 2024

It also addresses security, privacy concerns, and real-world applications across various industries, preparing students for careers in data analytics and fostering a deep understanding of Big Data’s impact. Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities.

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Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 12, 2024

Machine Learning with Python Machine Learning (ML) empowers systems to learn from data and improve their performance over time without explicit programming. Algorithms in ML identify patterns and make decisions, which is crucial for applications like predictive analytics and recommendation systems.

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Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Pickl AI

OCTOBER 15, 2024

Applications : Stock price prediction and financial forecasting Analysing sales trends over time Demand forecasting in supply chain management Clustering Models Clustering is an unsupervised learning technique used to group similar data points together. Popular clustering algorithms include k-means and hierarchical clustering.

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Decision Trees Hypothesis Testing Clustering Data Analysis 52

Heartbeat

OCTOBER 25, 2023

e) Big Data Analytics: The exponential growth of biological data presents challenges in storing, processing, and analyzing large-scale datasets. Supervised learning algorithms, such as support vector machines and random forests, have been extensively used in bioinformatics for tasks like classifying biological samples and predicting outcomes.

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Machine Learning Machine Learning Data Scientist Algorithm 52

Pickl AI

MAY 31, 2023

Accordingly, there are many Python libraries which are open-source including Data Manipulation, Data Visualisation, Machine Learning, Natural Language Processing , Statistics and Mathematics. Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow.

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Data Science Python Data Scientist Machine Learning 52

Pickl AI

NOVEMBER 18, 2024

Clustering and dimensionality reduction are common tasks in unSupervised Learning. For example, clustering algorithms can group customers by purchasing behaviour, even if the group labels are not predefined. Common Applications of Machine Learning Machine Learning has numerous applications across industries.

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Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

APRIL 9, 2025

DL Enhances Predictive Analytics: Excels in image and speech recognition tasks. Deep Learning Focuses on Neural Networks : Specializes in complex pattern recognition. AI Drives Automation and Efficiency : Improves processes across industries. Both Drive Technological Innovation: Transform industries with intelligent systems.

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Pickl AI

NOVEMBER 28, 2024

Support Vector Machines (SVM) SVMs are powerful classifiers that separate data into distinct categories by finding an optimal hyperplane. Key techniques in unsupervised learning include: Clustering (K-means) K-means is a clustering algorithm that groups data points into clusters based on their similarities.

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Machine Learning Machine Learning ML ML 52

Pickl AI

SEPTEMBER 23, 2024

Healthcare Data Science is revolutionising healthcare through predictive analytics, personalised medicine, and disease detection. Data Science continues to impact various industries, driving innovation and efficiency through data-driven insights and advanced analytics.

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Pickl AI

SEPTEMBER 12, 2024

C Classification: A supervised Machine Learning task that assigns data points to predefined categories or classes based on their characteristics. Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities.

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ODSC - Open Data Science

JANUARY 7, 2025

Both PyTorch and TensorFlow/Keras are still the go-to machine learning frameworks for a number of tasks, largely thanks to their ability to scale and be used for more resource-intensive tasks like deep learning; these two frameworks arent limited to just basic ML. Kafka remains the go-to for real-time analytics and streaming.

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Data Scientist Data Science Machine Learning Machine Learning 40

DagsHub

APRIL 21, 2024

Scikit-learn provides a consistent API for training and using machine learning models, making it easy to experiment with different algorithms and techniques. Grafana Grafana is a popular analytics and visualization platform that is most commonly used for monitoring and observability in machine learning.

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Machine Learning Machine Learning ML ML 59

Mlearning.ai

MAY 23, 2023

What is the difference between data analytics and data science? Data analytics deals with checking the existing hypothesis and information and answering questions for a better and more effective business-related decision-making process. Another example can be the algorithm of a support vector machine.

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How to Learn Machine Learning

MARCH 25, 2025

(Or even better than that) Machine learning has transformed the way businesses operate by automating processes, analyzing data patterns, and improving decision-making. It plays a crucial role in areas like customer segmentation, fraud detection, and predictive analytics. These are known as supervised learning and unsupervised learning.

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