Pickl AI

FEBRUARY 12, 2024

Here are some key areas often assessed: Programming Proficiency Candidates are often tested on their proficiency in languages such as Python, R, and SQL, with a focus on data manipulation, analysis, and visualization. Examples include linear regression, logistic regression, and support vector machines.

Data Science 52

Data Science Cross Validation Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

Understanding the differences between SQL and NoSQL databases is crucial for students. Statistical Analysis Introducing statistical methods and techniques for analysing data, including hypothesis testing, regression analysis, and descriptive statistics. Students should learn how to train and evaluate models using large datasets.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 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

Pickl AI

SEPTEMBER 12, 2024

Inferential Statistics: A branch of statistics that makes inferences about a population based on a sample, allowing for hypothesis testing and confidence intervals. Query: A request for information or data retrieval from a database, often written in a structured query language (SQL).

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Mlearning.ai

MAY 23, 2023

Another example can be the algorithm of a support vector machine. Hence, we have various classification algorithms in machine learning like logistic regression, support vector machine, decision trees, Naive Bayes classifier, etc. What are Support Vectors in SVM (Support Vector Machine)?

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52