Analytics Vidhya

JUNE 16, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Support Vector Machine (SVM) is one of the Machine Learning. The post The A-Z guide to Support Vector Machine appeared first on Analytics Vidhya.

Support Vector Machines 305

Support Vector Machines Machine Learning Machine Learning Data Science 305

Analytics Vidhya

OCTOBER 16, 2022

This article was published as a part of the Data Science Blogathon. Introduction Support vector machine is one of the most famous and decorated machine learning algorithms in classification problems.

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Support Vector Machines Algorithm Machine Learning Machine Learning 394

Dataconomy

APRIL 8, 2025

Data science techniques are the backbone of modern analytics, enabling professionals to transform raw data into meaningful insights. By employing various methodologies, analysts uncover hidden patterns, predict outcomes, and support data-driven decision-making. What are data science techniques?

Data Science 91

Data Science Support Vector Machines Data Scientist Data Visualization 91

Analytics Vidhya

MAY 20, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Before the sudden rise of neural networks, Support Vector Machines. The post Top 15 Questions to Test your Data Science Skills on SVM appeared first on Analytics Vidhya.

Data Science 229

Data Science Support Vector Machines Analytics Analytics 229

Data Science Dojo

JULY 15, 2024

By understanding machine learning algorithms, you can appreciate the power of this technology and how it’s changing the world around you! Let’s unravel the technicalities behind this technique: The Core Function: Regression algorithms learn from labeled data , similar to classification.

Machine Learning 307

Machine Learning Machine Learning Algorithm Clustering 307

Data Science Dojo

FEBRUARY 7, 2023

Top statistical techniques – Data Science Dojo Counterfactual causal inference: Counterfactual causal inference is a statistical technique that is used to evaluate the causal significance of historical events. These algorithms are often used to solve optimization problems, such as gradient descent and conjugate gradient.

Data Analysis 370

Data Analysis Data Analysis Support Vector Machines Algorithm 370

Data Science Dojo

MAY 24, 2023

Machine learning practices are the guiding principles that transform raw data into powerful insights. By following best practices in algorithm selection, data preprocessing, model evaluation, and deployment, we unlock the true potential of machine learning and pave the way for innovation and success.

Machine Learning 364

Machine Learning Machine Learning Data Scientist Support Vector Machines 364

Data Science Dojo

AUGUST 11, 2023

In contemporary times, data science has emerged as a substantial and progressively expanding domain that has an impact on virtually every sphere of human ingenuity: be it commerce, technology, healthcare, education, governance, and beyond. This piece will concentrate on the elemental constituents constituting data science.

Data Science 195

Data Science Python Data Scientist Decision Trees 195

Data Science Dojo

FEBRUARY 15, 2023

Image Credit: Pinterest – Problem solving tools In last week’s post , DS-Dojo introduced our readers to this blog-series’ three focus areas, namely: 1) software development, 2) project-management, and 3) data science. This week, we continue that metaphorical (learning) journey with a fun fact. Better yet, a riddle. IoT, Web 3.0,

K-nearest Neighbors 195

K-nearest Neighbors Decision Trees Support Vector Machines Data Science 195

Data Science Dojo

FEBRUARY 14, 2024

Feature Engineering is a process of using domain knowledge to extract and transform features from raw data. These features can be used to improve the performance of Machine Learning Algorithms. Here, we can observe a drastic improvement in our model accuracy when we apply the same algorithm to standardized features.

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K-nearest Neighbors Machine Learning Machine Learning Support Vector Machines 243

Data Science Dojo

MAY 27, 2024

A visual representation of generative AI – Source: Analytics Vidhya Generative AI is a growing area in machine learning, involving algorithms that create new content on their own. These algorithms use existing data like text, images, and audio to generate content that looks like it comes from the real world.

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Towards AI

JULY 15, 2024

R has simplified the most complex task of geospatial machine learning and data science. As GIS is slowly embracing data science, mastery of programming is very necessary regardless of your perception of programming. data = trainData) 5.

Machine Learning 119

Machine Learning Machine Learning Algorithm K-nearest Neighbors 119

Mlearning.ai

MAY 12, 2023

Support Vector Machine: A Comprehensive Guide — Part1 Support Vector Machines (SVMs) are a type of supervised learning algorithm used for classification and regression analysis. Submission Suggestions Support Vector Machine: A Comprehensive Guide — Part1 was originally published in MLearning.ai

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Support Vector Machines Natural Language Processing Supervised Learning Algorithm 52

Towards AI

FEBRUARY 23, 2024

Learn how to apply state-of-the-art clustering algorithms efficiently and boost your machine-learning skills.Image source: unsplash.com. In Data Science, clustering is used to group similar instances together, discovering patterns, hidden structures, and fundamental relationships within a dataset.

Clustering 115

Clustering Support Vector Machines Machine Learning Machine Learning 115

Mlearning.ai

MAY 22, 2023

Support Vector Machine: A Comprehensive Guide — Part2 In my last article, we discussed SVMs, the geometric intuition behind SVMs, and also Soft and Hard margins. So we can use SVM kernels here to transform the data into higher dimensions. But the model can create only 1 best-fit line. BECOME a WRITER at MLearning.ai.

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Support Vector Machines Machine Learning Machine Learning Algorithm 52

IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

FEBRUARY 2, 2025

For instance, a classification algorithm could predict whether a transaction is fraudulent or not based on various features. Role of Algorithms in Associative Classification Algorithms play a crucial role in associative classification by automating the rule generation, evaluation, and classification process.

Data Mining 52

Data Mining Data Mining Data Mining Decision Trees 52

Pickl AI

APRIL 6, 2025

Learn how they work and how to apply them in real-world projects through Pickl.AIs data science courses. Introduction Machine learning often struggles when the data isnt in a straight lineliterally! This is where kernel methods in machine learning come in like superheroes.

Machine Learning 52

Machine Learning Machine Learning Support Vector Machines Data Science 52

Data Science Dojo

APRIL 10, 2023

Selecting the right algorithm There are several data mining algorithms available, each with its strengths and weaknesses. When selecting an algorithm, consider factors such as the size and type of your dataset, the problem you’re trying to solve, and the computational resources available.

Data Mining 195

Data Mining Data Mining Data Mining Algorithm 195

ODSC - Open Data Science

FEBRUARY 13, 2023

The field of data science changes constantly, and some frameworks, tools, and algorithms just can’t get the job done anymore. Machine Learning for Beginners Learn the essentials of machine learning including how Support Vector Machines, Naive Bayesian Classifiers, and Upper Confidence Bound algorithms work.

Machine Learning 98

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Data Science Dojo

JULY 23, 2024

ML models often require numerical input, so categorical data must be converted into a numerical format for effective processing and analysis. Here are some key points highlighting the importance of categorical data in machine learning: 1. This conversion allows models to process the data and extract valuable information.

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Machine Learning Machine Learning Algorithm ML 195

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!

Machine Learning 98

Machine Learning Machine Learning Support Vector Machines Clustering 98

Pickl AI

FEBRUARY 12, 2024

Data Science interviews are pivotal moments in the career trajectory of any aspiring data scientist. Having the knowledge about the data science interview questions will help you crack the interview. Data Science skills that will help you excel professionally.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

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. Data Science enhances ML accuracy through preprocessing and feature engineering expertise.

Data Science 52

Data Science ML ML Machine Learning 52

Smart Data Collective

JUNE 7, 2019

Machine learning is playing a very important role in improving the functionality of task management applications. In January, Towards Data Science published an article on this very topic. “In Project managers should be aware of the changes that machine learning has brought to task management applications. Final Thoughts.

Machine Learning 101

Machine Learning Machine Learning Supervised Learning Support Vector Machines 101

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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Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. Introduction In the rapidly evolving field of Data Science, understanding key terminology is crucial for Data Analysts to communicate effectively, collaborate effectively, and drive data-driven projects.

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Data Analyst Data Science Machine Learning Machine Learning 52

Towards AI

APRIL 27, 2023

Understanding the Principles, Challenges, and Applications of Gradient Descent Image by Author with @MidJourney Introduction to Gradient Descent Gradient descent is a fundamental optimization algorithm used in machine learning and data science to find the optimal values of the parameters in a model.

Machine Learning 98

Machine Learning Machine Learning Support Vector Machines Algorithm 98

Pickl AI

MAY 31, 2023

With the expanding field of Data Science, the need for efficient and skilled professionals is increasing. Its efficacy may allow kids from a young age to learn Python and explore the field of Data Science. Its efficacy may allow kids from a young age to learn Python and explore the field of Data Science.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Mlearning.ai

MARCH 13, 2023

Photo by Andy Kelly on Unsplash Choosing a machine learning (ML) or deep learning (DL) algorithm for application is one of the major issues for artificial intelligence (AI) engineers and also data scientists. Explore algorithms: Research and explore different algorithms that are desired for your problem.

Machine Learning 52

Machine Learning Machine Learning Algorithm Support Vector Machines 52

Mlearning.ai

MAY 23, 2023

Hey guys, in this blog we will see some of the most asked Data Science Interview Questions by interviewers in [year]. Data science has become an integral part of many industries, and as a result, the demand for skilled data scientists is soaring. What is Data Science?

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Data Science Decision Trees Machine Learning Machine Learning 52

Mlearning.ai

APRIL 6, 2023

However, with a wide range of algorithms available, it can be challenging to decide which one to use for a particular dataset. will my data help in this ? If you can understand the data then you even do not need to use all algorithms. Let's understand this in detail.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

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.

K-nearest Neighbors 98

K-nearest Neighbors Algorithm Clustering Support Vector Machines 98

IBM Journey to AI blog

DECEMBER 20, 2023

Each type and sub-type of ML algorithm has unique benefits and capabilities that teams can leverage for different tasks. What is machine learning? ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

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.

Machine Learning 109

Machine Learning Machine Learning ML ML 109

AWS Machine Learning Blog

FEBRUARY 25, 2025

For the classfier, we employed a classic ML algorithm, k-NN, using the scikit-learn Python module. The following figure illustrates the F1 scores for each class plotted against the number of neighbors (k) used in the k-NN algorithm. The SVM algorithm requires the tuning of several parameters to achieve optimal performance.

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Algorithm Machine Learning Machine Learning K-nearest Neighbors 72

Towards AI

JULY 20, 2023

This ongoing process straddles the intersection between evidence-based medicine, data science, and artificial intelligence (AI). As the capabilities of high-powered computers and ML algorithms have grown, so have opportunities to improve the SLR process.

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