Pickl AI

MAY 31, 2023

Begin by employing algorithms for supervised learning such as linear regression , logistic regression, decision trees, and support vector machines. It includes regression, classification, clustering, decision trees, and more. To obtain practical expertise, run the algorithms on datasets.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

Pickl AI

APRIL 3, 2025

Modeling: Build a logistic regression or decision tree model to predict the likelihood of a customer churning based on various factors. Tools Commonly Used Business Intelligence Platforms: Tableau, Microsoft Power BI, Qlik Sense, Google Data Studio (Looker Studio) Programming Libraries: Matplotlib, Seaborn (Python); ggplot2 (R); D3.js

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

Pickl AI

APRIL 26, 2024

What are the advantages and disadvantages of decision trees ? Yes, I am proficient in data visualisation tools such as Tableau, Power BI, and Matplotlib in Python, which I use to create interactive and insightful visualisations for data analysis. Have you worked with cloud-based data platforms like AWS, Google Cloud, or Azure?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

DECEMBER 4, 2024

Dive Deep into Machine Learning and AI Technologies Study core Machine Learning concepts, including algorithms like linear regression and decision trees. Learn to use tools like Tableau, Power BI, or Matplotlib to create compelling visual representations of data. Additionally, familiarity with cloud platforms (e.g.,

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JULY 10, 2023

Esquisse: One of the most essential tableau features that has been introduced within the R libraries is Esquisse. Using caret, you can train and evaluate various algorithms, such as logistic regression, decision trees, and random forests, and select the best-performing model based on evaluation metrics like accuracy or AUC.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

AUGUST 9, 2024

Key topics include: Supervised Learning Understanding algorithms such as linear regression, decision trees, and support vector machines, and their applications in Big Data. Visualisation Tools Familiarity with tools such as Tableau, Power BI, and D3.js 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

ODSC - Open Data Science

JANUARY 7, 2025

Luckily, nothing too complicated is needed, as Tableau is user-friendly while matplotlib is the popular Python library for data visualization. Classification techniques like random forests, decision trees, and support vector machines are among the most widely used, enabling tasks such as categorizing data and building predictive models.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

SEPTEMBER 23, 2024

Machine Learning Supervised Learning includes algorithms like linear regression, decision trees, and support vector machines. Tableau: A leading Data Visualisation tool that allows users to create interactive and shareable dashboards.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Machine Learning 52

Pickl AI

FEBRUARY 13, 2025

Other hierarchical tools are tree diagrams, sunburnt diagrams, decision trees, and flow charts. Network Network tools are tools that allow you to visualise data that’s hard to capture using a tree structure. When presenting data this way, you can give items multiple attributes.

Data Visualization 52

Data Visualization Power BI Tableau Decision Trees 52