KDnuggets

APRIL 12, 2022

Also: Decision Tree Algorithm, Explained; 8 Free MIT Courses to Learn Data Science Online; Why Are So Many Data Scientists Quitting Their Jobs?; Top Programming Languages and Their Uses.

Decision Trees 271

Decision Trees Data Scientist Data Science Algorithm 271

Data Science Dojo

AUGUST 27, 2024

Data scientists use data to uncover patterns, trends, and insights that can help businesses make better decisions. A data scientist could analyze sales data, customer surveys, and social media trends to determine the reason. Handling Uncertainty: Data is often messy and incomplete.

Data Scientist 195

Data Scientist Data Science Machine Learning Machine Learning 195

Dataconomy

JULY 24, 2023

If you’ve found yourself asking, “How to become a data scientist?” In this detailed guide, we’re going to navigate the exciting realm of data science, a field that blends statistics, technology, and strategic thinking into a powerhouse of innovation and insights. What is a data scientist?

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

Towards AI

OCTOBER 3, 2024

A Comprehensive AI Guide All Machine Learning Engineers and Data Scientists Should Read! This is the essence of a decision tree—one of today’s most intuitive and powerful machine learning algorithms. This is the essence of a decision tree—one of today’s most intuitive and powerful machine learning algorithms.

Decision Trees 105

Decision Trees Machine Learning Machine Learning Algorithm 105

insideBIGDATA

APRIL 6, 2024

In this video presentation, our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, is joined by Kirill Eremenko to walk listeners through why decision trees and random forests are fruitful for businesses, and he offers hands-on walkthroughs for the three leading gradient-boosting algorithms today: XGBoost, (..)

Decision Trees 195

Decision Trees Data Scientist Machine Learning Machine Learning 195

KDnuggets

AUGUST 26, 2019

Understanding Decision Trees for Classification in Python; How to Become More Marketable as a Data Scientist; Is Kaggle Learn a Faster Data Science Education? Also: Deep Learning for NLP: Creating a Chatbot with Keras!;

Data Scientist 128

Data Scientist Decision Trees Deep Learning Deep Learning 128

KDnuggets

JANUARY 16, 2020

This post is about fast-tracking the study and explanation of tree concepts for the data scientists so that you breeze through the next time you get asked these in an interview.

Data Science 348

Data Science Algorithm Data Scientist Decision Trees 348

Data Science Dojo

SEPTEMBER 26, 2023

Learn about 33 tools to visualize data with this blog In this blog post, we will delve into some of the most important plots and concepts that are indispensable for any data scientist. 9 Data Science Plots – Data Science Dojo 1. Suppose you are a data scientist working for an e-commerce company.

Data Science 370

Data Science Clustering Decision Trees Power BI 370

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. They follow a top-down greedy approach to select the best feature for each split. What is the Gini Index?

Decision Trees 195

Decision Trees Machine Learning Machine Learning Algorithm 195

Towards AI

JULY 19, 2023

The American Owners in the eternal meeting [Image by the author + AI] Finally, a rumor began to circulate that the owners were locked away in a room with the top Data Scientists worldwide, analyzing every detail,… Read the full blog for free on Medium. Join thousands of data leaders on the AI newsletter.

Decision Trees 96

Decision Trees Data Scientist AI AI 96

Data Science Dojo

AUGUST 11, 2023

Statistics: Unveiling the patterns within data Statistics serves as the bedrock of data science, providing the tools and techniques to collect, analyze, and interpret data. It equips data scientists with the means to uncover patterns, trends, and relationships hidden within complex datasets.

Data Science 195

Data Science Python Data Scientist Decision Trees 195

Dataconomy

MAY 12, 2025

XGBoost has gained a formidable reputation in the realm of machine learning, becoming a go-to choice for practitioners and data scientists alike. Decision trees Decision trees form the backbone of XGBoost. Advantages of XGBoost Many attributes contribute to XGBoost’s preference among data scientists.

Decision Trees 91

Decision Trees Data Scientist Machine Learning Machine Learning 91

Data Science Dojo

JUNE 9, 2023

The job market for data scientists is booming. In fact, the demand for data experts is expected to grow by 36% between 2021 and 2031, significantly higher than the average for all occupations. This is great news for anyone who is interested in a career in data science. According to the U.S.

Data Science 370

Data Science Machine Learning Machine Learning Data Scientist 370

Towards AI

NOVEMBER 6, 2024

Gradient boosting involves training a series of weak learners (often decision trees) where each subsequent tree corrects the errors of the previous ones, creating a strong predictive model. This structure speeds up calculations and makes the model more interpretable.

Cross Validation 109

Cross Validation Decision Trees Algorithm Machine Learning 109

Dataconomy

MARCH 17, 2025

Unsupervised models Unsupervised models typically use traditional statistical methods such as logistic regression, time series analysis, and decision trees. These methods analyze data without pre-labeled outcomes, focusing on discovering patterns and relationships.

Decision Trees 91

Decision Trees Predictive Analytics Data Preparation Machine Learning 91

phData

MAY 19, 2023

Its visually appealing interface and the ability to add custom scripts in various programming languages make it a preferred choice among novice and seasoned data scientists. This post will delve into one of the many facets of KNIME’s capabilities –building predictive models using decision trees and random forests.

Decision Trees 52

Decision Trees Data Science Machine Learning Machine Learning 52

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. Tools such as Python, R, and SQL help to manipulate and analyze data. Statistics helps data scientists to estimate, predict and test hypotheses.

Data Science 195

Data Science Data Scientist Python Decision Trees 195

Dataconomy

MARCH 25, 2025

They provide a foundational understanding and a reference point from which data scientists can gauge the performance of advanced algorithms. Decision trees: Provide interpretable predictions based on logical rules. By understanding their performance, data scientists can design and refine complex algorithms effectively.

Decision Trees 91

Decision Trees Machine Learning Machine Learning Data Scientist 91

Dataconomy

MARCH 12, 2025

By providing a clear numerical representation of similarity, Hellinger Distance aids researchers and data scientists in understanding and analyzing complex problems with ease. In machine learning: – Improves decision tree algorithms, particularly in the node-splitting phase, adding precision to predictions.

Hypothesis Testing 103

Hypothesis Testing Machine Learning Machine Learning Decision Trees 103

Data Science Dojo

OCTOBER 15, 2023

To help you make an informed decision, here are detailed tips on how to select the ideal data science bootcamp for your unique needs: The challenge: Choosing the right data science bootcamp Outline your career goals: What do you want to do with a data science degree?

Data Science 195

Data Science Data Scientist Decision Trees Python 195

Data Science Dojo

AUGUST 30, 2023

Statistical analysis and hypothesis testing Statistical methods provide powerful tools for understanding data. An Applied Data Scientist must have a solid understanding of statistics to interpret data correctly. Machine learning algorithms Machine learning forms the core of Applied Data Science.

Data Science 195

Data Science Hypothesis Testing Machine Learning Machine Learning 195

Dataconomy

APRIL 21, 2025

During the data preprocessing phase, handling categorical data can consume considerable time for data scientists, making it a crucial aspect of model preparation. This includes converting categorical data into numerical values, which is often necessary for algorithms to work effectively.

Machine Learning 91

Machine Learning Machine Learning Algorithm Decision Trees 91

Pickl AI

FEBRUARY 2, 2025

It identifies hidden patterns in data, making it useful for decision-making across industries. Compared to decision trees and SVM, it provides interpretable rules but can be computationally intensive. Key applications include fraud detection, customer segmentation, and medical diagnosis.

Data Mining 52

Data Mining Data Mining Data Mining Decision Trees 52

Dataconomy

MARCH 12, 2025

By focusing on finding the optimal decision boundary between different classes of data, SVMs have stood out in both academic research and practical applications. Their ability to handle high-dimensional spaces and to create precise models in varied environments captures the interest of many data scientists and analysts.

Support Vector Machines 91

Support Vector Machines Decision Trees Supervised Learning Machine Learning 91

Pickl AI

APRIL 28, 2023

A Data Scientist’s average salary in India is up to₹ 8.0 Well, one of the key factors drawing attention towards the Data Scientist job profile is the higher pay package. In fact, the highest salary of a Data Scientist in India can be up to ₹ 26.0 Data Scientist Salary in Hyderabad : ₹ 8.0

Data Scientist 52

Data Scientist Data Science Hypothesis Testing Decision Trees 52

Pickl AI

NOVEMBER 2, 2023

A cheat sheet for Data Scientists is a concise reference guide, summarizing key concepts, formulas, and best practices in Data Analysis, statistics, and Machine Learning. It serves as a handy quick-reference tool to assist data professionals in their work, aiding in data interpretation, modeling , and decision-making processes.

Data Scientist 52

Data Scientist Data Science Data Visualization Machine Learning 52

Dataconomy

MARCH 28, 2025

Decision trees: They segment data into branches based on sequential questioning. Unsupervised algorithms In contrast, unsupervised algorithms analyze data without pre-existing labels, identifying inherent structures and patterns. Random forest: Combines multiple decision trees to strengthen predictive capabilities.

Machine Learning 91

Machine Learning Machine Learning Algorithm K-nearest Neighbors 91

Dataconomy

MARCH 26, 2025

Imbalanced data is a common issue faced by data scientists and machine learning practitioners. As the prevalence of data-driven decision-making increases, understanding the implications of imbalanced data is crucial for developing effective algorithms that can accurately classify observations despite uneven class distributions.

Machine Learning 91

Machine Learning Machine Learning Algorithm Decision Trees 91

Data Science Dojo

SEPTEMBER 13, 2024

Read more about classification using decision trees Threshold Selection In practice, ROC curves greatly help in the selection of the optimal threshold for classification problems.

Decision Trees 195

Decision Trees Data Scientist Machine Learning Machine Learning 195

Data Science Dojo

AUGUST 6, 2024

This process helps mitigate the high bias often seen in shallow decision trees and logistic regression models. By understanding and leveraging boosting algorithms applications, data scientists and machine learning practitioners can unlock new levels of performance in their predictive modelling endeavours.

Machine Learning 195

Machine Learning Machine Learning Algorithm ML 195

ODSC - Open Data Science

MARCH 11, 2025

But how can machine learning practitioners improve the reliability of their models, particularly when dealing with tabular data? Lucena attributes its dominance to the way gradient boosted decision trees (GBDTs) handle structured information.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Deep Learning 52

Smart Data Collective

SEPTEMBER 16, 2020

Data Sourcing. Fundamental to any aspect of data science, it’s difficult to develop accurate predictions or craft a decision tree if you’re garnering insights from inadequate data sources.

Predictive Analytics 139

Predictive Analytics Analytics Analytics Decision Trees 139

DrivenData Labs

MAY 24, 2023

Currently pursuing graduate studies at NYU's center for data science. Alejandro Sáez: Data Scientist with consulting experience in the banking and energy industries currently pursuing graduate studies at NYU's center for data science. We trained one LightGBM model per airport.

Machine Learning 225

Machine Learning Machine Learning Data Science Decision Trees 225

ODSC - Open Data Science

JANUARY 7, 2025

Heres what we noticed from analyzing this data, highlighting whats remained the same over the years, and what additions help make the modern data scientist in2025. Data Science Of course, a data scientist should know data science! Joking aside, this does infer particular skills.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Mlearning.ai

NOVEMBER 30, 2023

Mastering Tree-Based Models in Machine Learning: A Practical Guide to Decision Trees, Random Forests, and GBMs Image created by the author on Canva Ever wondered how machines make complex decisions? Just like a tree branches out, tree-based models in machine learning do something similar. So buckle up!

Machine Learning 52

Machine Learning Machine Learning Decision Trees Data Science 52

Pickl AI

SEPTEMBER 30, 2024

It builds multiple decision trees and merges them to produce accurate and stable predictions, making it a popular choice for complex data problems. Understanding these pros and cons will help you decide when to effectively utilise Random Forest in your Data Analysis projects. What is Random Forest?

Decision Trees 52

Decision Trees Algorithm Machine Learning Machine Learning 52

ODSC - Open Data Science

NOVEMBER 30, 2023

Most commercially available AI tools are black-box, meaning they do not cite what they generate or make it easy for data scientists to discover where the AI-derived information. It uses data mining techniques like decision trees and rule-based systems to generate correct responses.

AI 94

AI AI Data Scientist Decision Trees 94