Pickl AI

NOVEMBER 28, 2024

Concepts such as probability distributions, hypothesis testing , and Bayesian inference enable ML engineers to interpret results, quantify uncertainty, and improve model predictions. Decision Trees These trees split data into branches based on feature values, providing clear decision rules.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

MAY 31, 2023

Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines. After that, move towards unsupervised learning methods like clustering and dimensionality reduction. It includes regression, classification, clustering, decision trees, and more.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. Statistical Analysis Introducing statistical methods and techniques for analysing data, including hypothesis testing, regression analysis, and descriptive statistics.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

NOVEMBER 5, 2024

Statistical Knowledge A solid understanding of statistics is fundamental for analysing data distributions and conducting hypothesis testing. Mastery of these tools allows Data Scientists to efficiently process large datasets and develop robust models.

Data Science 52

Data Science Artificial Intelligence Artificial Intelligence Machine Learning 52

Pickl AI

MAY 30, 2024

It’s critical in harnessing data insights for decision-making, empowering businesses with accurate forecasts and actionable intelligence. Options include linear regression for continuous outcomes and decision trees for classification tasks. The choice impacts the model’s performance and accuracy.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Mlearning.ai

MAY 23, 2023

There are majorly two categories of sampling techniques based on the usage of statistics, they are: Probability Sampling techniques: Clustered sampling, Simple random sampling, and Stratified sampling. Decision trees are more prone to overfitting. Some algorithms that have low bias are Decision Trees, SVM, etc.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Pickl AI

APRIL 26, 2024

Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour. What are the advantages and disadvantages of decision trees ? You’re tasked with predicting sales for a retail store. What approach would you take?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

SEPTEMBER 23, 2024

Hypothesis testing and regression analysis are crucial for making predictions and understanding data relationships. Machine Learning Supervised Learning includes algorithms like linear regression, decision trees, and support vector machines.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Data Science Dojo

AUGUST 30, 2023

Statistical analysis and hypothesis testing Statistical methods provide powerful tools for understanding data. Hypothesis testing, correlation, and regression analysis, and distribution analysis are some of the essential statistical tools that data scientists use.

Data Science 195

Data Science Hypothesis Testing Machine Learning Machine Learning 195

Dataconomy

MARCH 12, 2025

In statistics: – Utilized for hypothesis testing to assess the validity of statistical models. – An effective tool in clustering and classification tasks, enhancing the performance of group analysis. – Addresses challenges presented by imbalanced datasets, which is crucial for refining classification tasks.

Hypothesis Testing 103

Hypothesis Testing Machine Learning Machine Learning Decision Trees 103