Monitoring Machine Learning in Python
This course covers everything you need to know to build a basic machine learning monitoring system in Python
Siga vídeos curtos conduzidos por instrutores especializados e pratique o que aprendeu com exercícios interativos em seu navegador.
This course covers everything you need to know to build a basic machine learning monitoring system in Python
Learn how to work with streaming data using serverless technologies on AWS.
Discover how the Pinecone vector database is revolutionizing AI application development!
Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.
In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.
Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.
Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.
Learn survey design using common design structures followed by visualizing and analyzing survey results.
Learn how to use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.
Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.
Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.
Learn how to efficiently collect and download data from any website using R.
Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.
Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.
Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!
Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.
Learn how to write recursive queries and query hierarchical data structures.
This Power BI case study follows a real-world business use case where you will apply the concepts of ETL and visualization.
Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.
Learn to use the KNIME Analytics Platform for data access, cleaning, and analysis with a no-code/low-code approach.
Learn how to design Power BI visualizations and reports with users in mind.
Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.
Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.
Learn how to access financial data from local files as well as from internet sources.
Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.
Explore o Controle de Versão de Dados para gestão de dados de ML. Configure, automatize e avalie modelos.
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.
Learn how to use Python to analyze customer churn and build a model to predict it.
Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.