Data Science Dojo

AUGUST 9, 2024

In data science and machine learning, decision trees are powerful models for both classification and regression tasks. It is a measure of impurity (non-homogeneity) widely used in decision trees. The feature with the highest information gain is chosen for the node. What is the Gini Index? What is Entropy?

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Pickl AI

JANUARY 21, 2025

Summary: Machine Learning algorithms enable systems to learn from data and improve over time. Key examples include Linear Regression for predicting prices, Logistic Regression for classification tasks, and Decision Trees for decision-making. These intelligent predictions are powered by various Machine Learning algorithms.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

IBM Journey to AI blog

APRIL 13, 2023

In this post, I will show how to develop, deploy, and use a decision tree model in a Db2 database. For each flight, the dataset has information such as the flight’s origin airport, departure time, flying time, and arrival time. Also, a column in the dataset indicates if each flight had arrived on time or late.

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Towards AI

NOVEMBER 6, 2024

This story explores CatBoost, a powerful machine-learning algorithm that handles both categorical and numerical data easily. CatBoost is a powerful, gradient-boosting algorithm designed to handle categorical data effectively. CatBoost is part of the gradient boosting family, alongside well-known algorithms like XGBoost and LightGBM.

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Cross Validation Decision Trees Algorithm Machine Learning 109

Dataconomy

MARCH 4, 2025

By creating artificial datasets that mimic real-world statistics without compromising personal information, organizations can harness the power of data while adhering to stringent privacy regulations. Synthetic data is revolutionizing the way we approach data privacy and analysis across various industries. What is synthetic data?

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Data Science Dojo

AUGUST 27, 2024

In essence, data scientists use their skills to turn raw data into valuable information that can be used to improve products, services, and business strategies. Missing Data: Filling in missing pieces of information. Data-Driven Decisions: Based on these insights, data scientists can make informed decisions that drive business growth.

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Data Scientist Data Science Machine Learning Machine Learning 273

Pickl AI

JUNE 2, 2023

One of the most popular algorithms in Machine Learning are the Decision Trees that are useful in regression and classification tasks. Decision trees are easy to understand, and implement therefore, making them ideal for beginners who want to explore the field of Machine Learning. How Decision Tree Algorithm works?

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Dataconomy

MARCH 17, 2025

Through various statistical methods and machine learning algorithms, predictive modeling transforms complex datasets into understandable forecasts. Unsupervised models Unsupervised models typically use traditional statistical methods such as logistic regression, time series analysis, and decision trees.

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Decision Trees Predictive Analytics Data Preparation Machine Learning 91

Pickl AI

APRIL 13, 2025

Summary: Classifier in Machine Learning involves categorizing data into predefined classes using algorithms like Logistic Regression and Decision Trees. Classifiers are algorithms designed to perform this task efficiently, helping industries solve problems like spam detection, fraud prevention, and medical diagnosis.

Machine Learning 52

Machine Learning Machine Learning Decision Trees K-nearest Neighbors 52

Dataconomy

MARCH 4, 2025

Data mining refers to the systematic process of analyzing large datasets to uncover hidden patterns and relationships that inform and address business challenges. By utilizing algorithms and statistical models, data mining transforms raw data into actionable insights.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

Data Science Dojo

AUGUST 19, 2024

Business Benefits: Organizations are recognizing the value of AI and data science in improving decision-making, enhancing customer experiences, and gaining a competitive edge An AI research scientist acts as a visionary, bridging the gap between human intelligence and machine capabilities. Privacy: Protecting user privacy and data security.

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Dataconomy

APRIL 21, 2025

Knowing how to work with categorical variables can enhance the performance of machine learning models by ensuring that all available information is utilized effectively. They influence the choice of algorithms and the structure of models. Understanding specific needs and capabilities can help in effectively applying these algorithms.

Machine Learning 91

Machine Learning Machine Learning Algorithm Decision Trees 91

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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phData

MAY 19, 2023

But in its raw form, this data is just noise until it is analyzed and transformed into meaningful information. As an interdisciplinary field, data science leverages scientific methods, algorithms, and systems to extract insights from structured and unstructured data. This is where data science steps in.

Decision Trees 52

Decision Trees Data Science Machine Learning Machine Learning 52

Pickl AI

AUGUST 16, 2023

In the world of Machine Learning and Data Analysis , decision trees have emerged as powerful tools for making complex decisions and predictions. These tree-like structures break down a problem into smaller, manageable parts, enabling us to make informed choices based on data. What is a Decision Tree?

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Decision Trees Algorithm Machine Learning Machine Learning 52

Data Science Dojo

FEBRUARY 14, 2024

These features can be used to improve the performance of Machine Learning Algorithms. By manipulating the input features of a dataset, we can enhance their quality, extract meaningful information, and improve the performance of predictive models. This dataset includes four input features: User ID, Gender, Age, and Salary.

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Dataconomy

MAY 20, 2025

Extrapolation and interpolation are powerful tools in data analysis, enabling professionals to make informed predictions and fill in gaps in datasets. Extrapolation and interpolation serve as methods for estimating unknown data points based on existing information. What are extrapolation and interpolation?

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Predictive Analytics Decision Trees Data Analysis Data Analysis 91

Dataconomy

APRIL 29, 2025

Overview of classification in machine learning Classification serves as a foundational method in machine learning, where algorithms are trained on labeled datasets to make predictions. Classification methods are vital for organizing information and making data-driven decisions.

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Support Vector Machines Machine Learning Machine Learning Algorithm 91

Data Science Dojo

AUGUST 27, 2024

In essence, data scientists use their skills to turn raw data into valuable information that can be used to improve products, services, and business strategies. Meaningful Insights: Statistics helps to extract valuable information from the data, turning raw numbers into actionable insights. It’s like deciphering a secret code.

Data Scientist 195

Data Scientist Data Science Machine Learning Machine Learning 195

Data Science Dojo

AUGUST 11, 2023

Throughout the course of history, the significance of creating and disseminating information has been immensely crucial. Moreover, statistical inference empowers them to make informed decisions and draw meaningful conclusions based on sample data. It provides a wide range of mathematical functions and algorithms.

Data Science 195

Data Science Python Data Scientist Decision Trees 195

Data Science Dojo

JULY 23, 2024

Categorical data is one such form of information that is handled by ML models using different methods. Model Compatibility Most machine learning algorithms work with numerical data, making it essential to transform categorical variables into numerical values. Learn about 101 ML algorithms for data science with cheat sheets 5.

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Machine Learning Machine Learning Algorithm ML 195

Dataconomy

MARCH 12, 2025

Support Vector Machines (SVM) are a type of supervised learning algorithm designed for classification and regression tasks. This decision boundary is crucial for achieving accurate predictions and effectively dividing data points into categories. What are Support Vector Machines (SVM)?

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Support Vector Machines Decision Trees Supervised Learning Machine Learning 91

Towards AI

JANUARY 11, 2024

In this article, I’ve covered one of the most famous classification and regression algorithms in machine learning, namely the Decision Tree. This often occurs in Cluster Analysis, where we identify clusters without prior information. Before we start, please consider following me on Medium or LinkedIn.

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Machine Learning Machine Learning Decision Trees Supervised Learning 130

Google Research AI blog

FEBRUARY 7, 2023

The explosion in deep learning a decade ago was catapulted in part by the convergence of new algorithms and architectures, a marked increase in data, and access to greater compute. Below, we highlight a panoply of works that demonstrate Google Research’s efforts in developing new algorithms to address the above challenges.

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Towards AI

JULY 15, 2024

We shall look at various machine learning algorithms such as decision trees, random forest, K nearest neighbor, and naïve Bayes and how you can install and call their libraries in R studios, including executing the code.

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Machine Learning Machine Learning Algorithm K-nearest Neighbors 116

Data Science Dojo

JULY 7, 2023

This discipline takes raw data, deciphers it, and turns it into a digestible format using various tools and algorithms. Understanding algorithms is like mastering maps, with each algorithm offering different paths to solutions. Tools such as Python, R, and SQL help to manipulate and analyze data. The learning curve also varies.

Data Science 195

Data Science Data Scientist Python Algorithm 195

Flipboard

MAY 25, 2025

Feature selection via the Boruta and LASSO algorithms preceded the construction of predictive models using Random Forest, Decision Tree, K-Nearest Neighbors, Support Vector Machine, LightGBM, and XGBoost. Demographic data, physiological status, and non-invasive test indicators were collected.

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K-nearest Neighbors Machine Learning Machine Learning Support Vector Machines 81

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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Data Mining Data Mining Data Mining Algorithm 195

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

PyImageSearch

JANUARY 16, 2023

Setting Up Our Project Comparing XGboost and Gradient Boost Results Summary Citation Information Scaling Kaggle Competitions Using XGBoost: Part 3 We continue our journey into understanding XGBoost, but there is one penultimate stop we need to make before deep diving into the nitty gritty of Extreme Gradient Boosting.

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Analytics Vidhya

NOVEMBER 8, 2020

This article was published as a part of the Data Science Blogathon. Introduction Entropy is one of the key aspects of Machine Learning. The post Entropy – A Key Concept for All Data Science Beginners appeared first on Analytics Vidhya.

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Data Science Machine Learning Machine Learning Analytics 378

Towards AI

JULY 17, 2023

Later on, we will train a classifier for Car Evaluation data, by Encoding the data, Feature extraction and Developing classifier model using various algorithms and evaluate the results. Pyspark MLlib is a wrapper over PySpark Core to do data analysis using machine-learning algorithms. It works on distributed systems and is scalable.

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IBM Journey to AI blog

AUGUST 9, 2024

Predictive AI blends statistical analysis with machine learning algorithms to find data patterns and forecast future outcomes. In short, predictive AI helps enterprises make informed decisions regarding the next step to take for their business. What is predictive AI? Regression models determine correlations between variables.

AI 120

AI AI Decision Trees Algorithm 120

Dataconomy

MAY 25, 2023

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. This enables them to extract valuable insights, identify patterns, and make informed decisions in real-time.

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Pickl AI

JULY 7, 2023

Are you ready to take your machine learning algorithms to the next level? Say hello to Gradient Boosting Algorithm! Gradient boosting is not just your regular algorithm; it’s a functional gradient algorithm that works wonders in the world of machine learning. What is Gradient Boosting?

Algorithm 52

Algorithm Decision Trees Machine Learning Machine Learning 52

Dataconomy

JUNE 13, 2023

Making the right decisions in an aggressive market is crucial for your business growth and that’s where decision intelligence (DI) comes to play. In this era of information overload, utilizing the power of data and technology has become paramount to drive effective decision-making. What is decision intelligence?

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Pickl AI

SEPTEMBER 30, 2024

Summary: Random Forest is an effective Machine Learning algorithm known for its high accuracy and robustness. Introduction Random Forest is a powerful ensemble learning algorithm widely used in Machine Learning for classification and regression tasks. A single decision tree can be prone to errors and overfitting.

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