Data Science Dojo

AUGUST 19, 2024

Bureau of Labor Statistics predicting a 35% increase in job openings from 2022 to 2032. Python Explain the steps involved in training a decision tree. The demand for AI scientist is projected to grow significantly in the coming years, with the U.S. Technical Skills Implement a simple linear regression model from scratch.

AI 364

AI AI Machine Learning Machine Learning 364

Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? The information from previous decisions is analyzed via the decision tree.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? The information from previous decisions is analyzed via the decision tree.

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Pickl AI

JANUARY 29, 2024

ML focuses on algorithms like decision trees, neural networks, and support vector machines for pattern recognition. Skills Proficiency in programming languages (Python, R), statistical analysis, and domain expertise are crucial. billion in 2022 to a remarkable USD 484.17 billion by 2029. throughout the forecast period.

Data Science 52

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Pickl AI

SEPTEMBER 3, 2023

Further, it will provide a step-by-step guide on anomaly detection Machine Learning python. CAGR during 2022-2030. An ensemble of decision trees is trained on both normal and anomalous data. How to do Anomaly Detection using Machine Learning in Python? Billion which is supposed to increase by 35.6%

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Pickl AI

NOVEMBER 18, 2024

billion in 2022 and is expected to grow significantly, reaching USD 505.42 For example, linear regression is typically used to predict continuous variables, while decision trees are great for classification and regression tasks. Decision trees are easy to interpret but prone to overfitting.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 52

PyImageSearch

DECEMBER 12, 2022

We went through the core essentials required to understand XGBoost, namely decision trees and ensemble learners. Since we have been dealing with trees, we will assume that our adaptive boosting technique is being applied to decision trees. Looking for the source code to this post? Table 1: The Dataset. Raha, and A.

Decision Trees 52

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Pickl AI

NOVEMBER 28, 2024

Key programming languages include Python and R, while mathematical concepts like linear algebra and calculus are crucial for model optimisation. billion in 2022 and is expected to grow to USD 505.42 Key Takeaways Strong programming skills in Python and R are vital for Machine Learning Engineers. during the forecast period.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Heartbeat

SEPTEMBER 13, 2023

Here's an example of calculating feature importance using permutation importance with scikit-learn in Python: from sklearn.inspection import permutation_importance # Fit your model (e.g., Decision trees can be trained and visualized in rule-based explanations to reveal the underlying decision logic. Russell, C. &

Machine Learning 52

Machine Learning Machine Learning AI AI 52

Mlearning.ai

APRIL 17, 2023

Below is a detailed post on correlation analysis in Python. It is similar to the random forest in that it combines multiple decision trees to create a strong learner. It iteratively builds a sequence of decision trees, where each tree is trained to correct the errors made by the previous trees in the sequence.

Decision Trees 52

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Mlearning.ai

APRIL 13, 2023

Gaussian kernels are commonly used for classification problems that involve non-linear boundaries, such as decision trees or neural networks. Laplacian Kernels Laplacian kernels, also known as Laplacian of Gaussian (LoG) kernels, are used in decision trees or neural networks like image processing for edge detection.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Support Vector Machines 52

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

Hacker News

JUNE 29, 2025

It's a programming language designed for writing good CLI scripts, so it's aiming to replace Bash but is much more Python-like, and offers unique syntax and a bunch of in-built support for scripting. Uses lldb's Python scripting extensions to register commands, and handle memory access. This one is an itch.

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AI AI Database Python 75