Data Science Dojo

AUGUST 11, 2023

Machine learning is a field of computer science that uses statistical techniques to build models from data. The ability to understand the principles of probability, hypothesis testing, and confidence intervals enables data scientists to validate their findings and ascertain the reliability of their analyses.

Data Science 195

Data Science Python Data Scientist Decision Trees 195

Pickl AI

FEBRUARY 12, 2024

Statistical Concepts A strong understanding of statistical concepts, including probability, hypothesis testing, regression analysis, and experimental design, is paramount in Data Science roles. Examples include linear regression, logistic regression, and support vector machines.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

MAY 31, 2023

Explore Machine Learning with Python: Become familiar with prominent Python artificial intelligence libraries such as sci-kit-learn and TensorFlow. Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Mlearning.ai

MAY 23, 2023

Decision trees are more prone to overfitting. Underfitting: Here, the model is so simple that it is not able to identify the correct relationship in the data, and hence it does not perform well even on the test data. Some algorithms that have low bias are Decision Trees, SVM, etc. character) is underlined or not.

Data Science 52

Data Science Decision Trees Deep Learning Deep Learning 52