Pickl AI

FEBRUARY 12, 2024

Machine Learning Algorithms Candidates should demonstrate proficiency in a variety of Machine Learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, and neural networks. What is cross-validation, and why is it used in Machine Learning?

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Towards AI

JULY 19, 2023

That post was dedicated to an exploratory data analysis while this post is geared towards building prediction models. In our exercise, we will try to deal with this imbalance by — Using a stratified k-fold cross-validation technique to make sure our model’s aggregate metrics are not too optimistic (meaning: too good to be true!)

Machine Learning 40

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

Mlearning.ai

FEBRUARY 15, 2023

While the amount of data available was limited, we have tried to solve the problem of generalization by using methods such as stopwords removal, tokenization, lemmatization, dropout and early stopping. Prediction of Solar Irradiation Using Quantum Support Vector Machine Learning Algorithm. link] Ganaie, M.

Cross Validation 52

Cross Validation Decision Trees Natural Language Processing Algorithm 52

Heartbeat

OCTOBER 23, 2023

Image from "Big Data Analytics Methods" by Peter Ghavami Here are some critical contributions of data scientists and machine learning engineers in health informatics: Data Analysis and Visualization: Data scientists and machine learning engineers are skilled in analyzing large, complex healthcare datasets.

Machine Learning 52

Machine Learning Machine Learning Data Scientist Big Data Analytics 52

Mlearning.ai

MAY 23, 2023

The following Venn diagram depicts the difference between data science and data analytics clearly: 3. Data analysis can not be done on a whole volume of data at a time especially when it involves larger datasets. Another example can be the algorithm of a support vector machine.

Data Science 52

Data Science Decision Trees Deep Learning Deep Learning 52

Dataconomy

SEPTEMBER 1, 2023

So how can the technology of our time, machine learning, be used to improve the quality and length of human life? Heart disease stands as one of the foremost global causes of mortality today, presenting a critical challenge in clinical data analysis. Dealing with missing values is a common challenge in medical data analysis.

Decision Trees 195

Decision Trees Machine Learning Machine Learning Support Vector Machines 195

DagsHub

APRIL 21, 2024

Scikit-learn Scikit-learn is a machine learning library in Python that is majorly used for data mining and data analysis. It also provides tools for model evaluation , including cross-validation, hyperparameter tuning, and metrics such as accuracy, precision, recall, and F1-score.

Machine Learning 59

Machine Learning Machine Learning ML ML 59