Towards AI

JUNE 19, 2024

Last Updated on June 22, 2024 by Editorial Team Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. – Algorithms: Support Vector Machines (SVM), Random Forest, Neural Networks. – Algorithms: K-means Clustering, ISODATA. Deciding What Algorithm to Use for Earth Observation.

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Algorithm Clustering Support Vector Machines Machine Learning 81

Towards AI

APRIL 14, 2023

Last Updated on April 17, 2023 by Editorial Team Author(s): Kevin Berlemont, PhD Originally published on Towards AI. The feature space reduction is performed by aggregating clusters of features of balanced size. This clustering is usually performed using hierarchical clustering.

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K-nearest Neighbors Algorithm Clustering Support Vector Machines 98

Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

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K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

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 133

Towards AI

FEBRUARY 20, 2024

Last Updated on February 20, 2024 by Editorial Team Author(s): Vaishnavi Seetharama Originally published on Towards AI. 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.

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IBM Journey to AI blog

DECEMBER 19, 2023

Machine learning algorithms for unstructured data include: K-means: This algorithm is a data visualization technique that processes data points through a mathematical equation with the intention of clustering similar data points. Isolation forest models can be found on the free machine learning library for Python, scikit-learn.

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Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Pickl AI

AUGUST 1, 2023

Examples of supervised learning models include linear regression, decision trees, support vector machines, and neural networks. Common examples include: Linear Regression: It is the best Machine Learning model and is used for predicting continuous numerical values based on input features.

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Machine Learning Machine Learning Support Vector Machines Decision Trees 52

Mlearning.ai

FEBRUARY 17, 2023

But I also want truly define that ML isn’t represent some kind of unsecured AI technologies, super brain or dark magic, it’s clear combination of programming skills, enough amount of data, cloud solutions, theory of algorithms and math  — that’s all we should have to be able to work in this branch. In this article, I will cover all of them.

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Machine Learning Machine Learning K-nearest Neighbors Clustering 52

Mlearning.ai

APRIL 8, 2023

What is Natural Language Processing (NLP) Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that deals with interactions between computers and human languages. The earlier models that were SOTA for NLP mainly fell under the traditional machine learning algorithms. BECOME a WRITER at MLearning.ai

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Pickl AI

JULY 12, 2024

Introduction Artificial Intelligence (AI) transforms industries by enabling machines to mimic human intelligence. Python’s simplicity, versatility, and extensive library support make it the go-to language for AI development. Python’s strength in AI development lies in its rich ecosystem of libraries.

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Artificial Intelligence Artificial Intelligence Python Natural Language Processing 52

Dataconomy

JUNE 13, 2023

AI algorithms play a crucial role in decision intelligence. Rule-based systems, optimization techniques, or probabilistic frameworks are employed to guide decision-making based on the insights gained from data analysis and AI algorithms. How does decision intelligence work?

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Dataconomy

AUGUST 31, 2023

Machine learning models have already started to take up a lot of space in our lives, even if we are not consciously aware of it. Embracing AI systems and technology day by day, humanity is experiencing perhaps the fastest development in recent years. You want an example: ChatGPT, Alexa, autonomous vehicles and many more on the way.

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Dataconomy

MARCH 13, 2023

The creation of artificial intelligence (AI) has long been a dream of scientists, engineers, and innovators. With advances in machine learning, deep learning, and natural language processing, the possibilities of what we can create with AI are limitless. AI models can range from simple linear models to complex neural networks.

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Artificial Intelligence Artificial Intelligence Natural Language Processing Algorithm 98

Dataconomy

AUGUST 9, 2023

While network traffic analysis has traditionally involved many careful steps but today AI and ML applications have both accelerated and simplified this process ( Image credit ) Network traffic analysis is traditionally a multi-stage and complicated process.

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Machine Learning Machine Learning ML ML 91

Pickl AI

AUGUST 1, 2023

It helps in discovering hidden patterns and organizing text data into meaningful clusters. Machine Learning algorithms, including Naive Bayes, Support Vector Machines (SVM), and deep learning models, are commonly used for text classification. within the text.

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Data Analysis Data Analysis Python Support Vector Machines 52

Pickl AI

NOVEMBER 20, 2024

Practical Applications of Linear Algebra in Machine Learning Discover the practical applications of Linear Algebra in Machine Learning, including data preprocessing, model training, dimensionality reduction, and clustering. Model Training Most Machine Learning models rely heavily on Linear Algebra during training phases.

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Machine Learning Machine Learning Natural Language Processing Clustering 52

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. How do you handle missing values in a dataset?

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Pickl AI

SEPTEMBER 3, 2023

In 2023, the expected reach of the AI market is supposed to reach the $500 billion mark and in 2030 it is supposed to reach $1,597.1 49% of companies in the world that use Machine Learning and AI in their marketing and sales processes apply it to identify the prospects of sales.

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Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Pickl AI

AUGUST 6, 2024

Clustering Algorithms Techniques such as K-means clustering can help identify groups of similar data points. Points that do not belong to any cluster may be considered anomalies. Support Vector Machines (SVM) SVM can be employed for anomaly detection by finding the hyperplane that best separates normal data from anomalies.

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Data Quality Clustering Support Vector Machines Algorithm 52

Pickl AI

AUGUST 22, 2023

This harmonization is particularly critical in algorithms such as k-Nearest Neighbors and Support Vector Machines, where distances dictate decisions. Scaling steps in as a guardian, harmonizing the scales and ensuring that algorithms treat each feature fairly.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Pickl AI

FEBRUARY 7, 2025

Summary: Machine Learning and Deep Learning are AI subsets with distinct applications. Understanding their differences helps choose the right approach for AI-driven innovations across various industries. What is Machine Learning? Clustering and anomaly detection are examples of unsupervised learning tasks.

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Mlearning.ai

JUNE 8, 2023

Hidden secret to empower semantic search This is the third article of building LLM-powered AI applications series. To enable semantic search, we need something called embedding/vector/vector embedding. Meet AI's multitool: Vector embeddings | Google Cloud Blog Embedding applications Recommendation systems (i.e.

Machine Learning 52

Machine Learning Machine Learning Clustering Database 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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Pickl AI

NOVEMBER 18, 2024

Ethical considerations are crucial in developing fair Machine Learning solutions. Basics of Machine Learning Machine Learning is a subset of Artificial Intelligence (AI) that allows systems to learn from data, improve from experience, and make predictions or decisions without being explicitly programmed.

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Machine Learning Machine Learning Decision Trees Algorithm 52

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.

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Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. Big Data Technologies and Tools A comprehensive syllabus should introduce students to the key technologies and tools used in Big Data analytics.

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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.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

ODSC - Open Data Science

JANUARY 7, 2025

Deep Learning Deep learning is a cornerstone of modern AI, and its applications are expanding rapidly. Natural Language Processing (NLP) has emerged as a dominant area, with tasks like sentiment analysis, machine translation, and chatbot development leading the way.

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Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

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Pickl AI

SEPTEMBER 12, 2024

Artificial Intelligence (AI): A branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. Association Rule Learning: A rule-based Machine Learning method to discover interesting relationships between variables in large databases.

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DagsHub

DECEMBER 23, 2024

This allows organizations to grow their AI capabilities more efficiently without needing to rebuild their entire data collection and labeling process for each new use case.  This allows it to evaluate and find relationships between the data points which is essential for clustering. 

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Pickl AI

DECEMBER 9, 2024

Every Machine Learning algorithm, whether a decision tree, support vector machine, or deep neural network, inherently favours certain solutions over others. Algorithmic Bias Algorithmic bias arises from the design of the learning algorithm itself.

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Machine Learning Machine Learning Decision Trees Natural Language Processing 52

DagsHub

APRIL 21, 2024

Especially in the current time when LLM models are making their way for several industry-based generative AI projects. PyTorch Developed by Facebook’s AI Research Lab (FAIR), PyTorch is a popular machine-learning framework that offers a flexible and dynamic approach to building and training neural networks.

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Pickl AI

JANUARY 12, 2025

Summary: The article explores the differences between data driven and AI driven practices. Data-driven and AI-driven approaches have become key in how businesses address challenges, seize opportunities, and shape their strategic directions.

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AWS Machine Learning Blog

FEBRUARY 25, 2025

AI now plays a pivotal role in the development and evolution of the automotive sector, in which Applus+ IDIADA operates. In this post, we showcase the research process undertaken to develop a classifier for human interactions in this AI-based environment using Amazon Bedrock.

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