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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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

Ocean Protocol

NOVEMBER 28, 2024

The challenge demonstrated the intersection of sports and data science by combining real-world datasets with predictive modeling. 2nd Place: Yuichiro “Firepig” [Japan] Firepig created a three-step model that used decision trees, linear regression, and random forests to predict tire strategies, laps per stint, and average lap times.

Cross Validation 85

Cross Validation Decision Trees Data Scientist Data Science 85

Pickl AI

MAY 24, 2023

To help you understand Python Libraries better, the blog will explain a Python Libraries for Data Science List which you can learn about. This may include for instance in Machine Learning, Data Science, Data Visualisation, image and Data Manipulation. What is a Python Library?

Data Science 52

Data Science Python Machine Learning Machine Learning 52

DrivenData Labs

MAY 22, 2024

Unlike typical data science competitions, there's no predefined training dataset provided. This means participants must not only focus on modeling but also on finding the right data to be used. Forecast skill will be evaluated in August when the ground truth data becomes available.

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Heartbeat

OCTOBER 31, 2023

Before continuing, revisit the lesson on decision trees if you need help understanding what they are. We can compare the performance of the Bagging Classifier and a single Decision Tree Classifier now that we know the baseline accuracy for the test dataset. Bagging is a development of this idea.

Decision Trees 52

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Pickl AI

MAY 17, 2023

K-fold Cross Validation ML experts use cross-validation to resolve the issue. For this, the dataset is divided into two categories: test and train data. This model is tested to check the performance of the test data. Pickl.AI’s Data Science Courses offer a comprehensive learning module.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

NOVEMBER 2, 2023

It serves as a handy quick-reference tool to assist data professionals in their work, aiding in data interpretation, modeling , and decision-making processes. In the fast-paced world of Data Science, having quick and easy access to essential information is invaluable when using a repository of Cheat sheets for Data Scientists.

Data Scientist 52

Data Scientist Data Science Data Visualization Machine Learning 52

Pickl AI

FEBRUARY 19, 2025

It works by training multiple weak models (often decision trees with one split, known as stumps). Due to its high accuracy, XGBoost is widely used in data science competitions and practical applications like customer churn prediction and sales forecasting. Lets explore some of the most popular ones.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 52

Pickl AI

DECEMBER 12, 2024

Introduction Boosting is a powerful Machine Learning ensemble technique that combines multiple weak learners, typically decision trees, to form a strong predictive model. These features collectively make XGBoost a robust, high-performance tool for modern Data Science challenges. Lower values (e.g.,

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

Pickl AI

OCTOBER 15, 2024

They identify patterns in existing data and use them to predict unknown events. Techniques like linear regression, time series analysis, and decision trees are examples of predictive models. In more complex cases, you may need to explore non-linear models like decision trees, support vector machines, or time series models.

Decision Trees 52

Decision Trees Hypothesis Testing Clustering Data Analysis 52

Pickl AI

NOVEMBER 28, 2024

Decision Trees These trees split data into branches based on feature values, providing clear decision rules. Model Evaluation and Tuning After building a Machine Learning model, it is crucial to evaluate its performance to ensure it generalises well to new, unseen data.

Machine Learning 52

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Pickl AI

FEBRUARY 4, 2024

From linear regression to decision trees, Alteryx provides robust statistical models for forecasting trends and making informed decisions. Alteryx’s validation tools, such as the Cross-Validation Tool, ensure the accuracy and reliability of predictive models.

Data Preparation 52

Data Preparation Tableau Data Visualization Analytics 52

Pickl AI

AUGUST 9, 2024

Key topics include: Supervised Learning Understanding algorithms such as linear regression, decision trees, and support vector machines, and their applications in Big Data. Model Evaluation Techniques for evaluating machine learning models, including cross-validation, confusion matrix, and performance metrics.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Mlearning.ai

APRIL 13, 2023

The transformed data is then passed through a non-linear activation function to classify the data. Gaussian kernels are commonly used for classification problems that involve non-linear boundaries, such as decision trees or neural networks. This is often done using techniques such as cross-validation or grid search.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Support Vector Machines 52

Pickl AI

APRIL 26, 2024

Overfitting occurs when a model learns the training data too well, including noise and irrelevant patterns, leading to poor performance on unseen data. Techniques such as cross-validation, regularisation , and feature selection can prevent overfitting. What are the advantages and disadvantages of decision trees ?

Data Analyst 52

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Heartbeat

MAY 29, 2023

Transfer learning uses knowledge acquired from previous training and applies it to a new task; image from data-science-blog.com Transfer learning can also help to mitigate the problem of data sparsity, where the model is trained on a small number of examples that may not be representative of the true distribution of the data.

Machine Learning 78

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Mlearning.ai

JANUARY 29, 2024

Data Science Project — Build a Decision Tree Model with Healthcare Data Using Decision Trees to Categorize Adverse Drug Reactions from Mild to Severe Photo by Maksim Goncharenok Decision trees are a powerful and popular machine learning technique for classification tasks.

Decision Trees 52

Decision Trees Data Science Exploratory Data Analysis Data Analysis 52

DrivenData Labs

MAY 1, 2025

Our professional work involves processing and analyzing medical data, particularly focusing on image and audio data. Beyond our primary roles, we are enthusiastic participants in data science competitions and have achieved multiple victories in these contests. Fangjing Wu is a data science master's student.

Decision Trees 147

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Towards AI

JULY 19, 2023

(Check out the previous post to get a primer on the terms used) Outline Dealing with Class Imbalance Choosing a Machine Learning model Measures of Performance Data Preparation Stratified k-fold Cross-Validation Model Building Consolidating Results 1. among supervised models and k-nearest neighbors, DBSCAN, etc.,

Machine Learning 40

Machine Learning Machine Learning K-nearest Neighbors Support Vector Machines 40