Interactive ML Dashboards using Plotly Dash
The course concentrates on the development of an HTML framework for a Plotly Dash dashboard that includes interactive scatter plots, bar charts, radio buttons, and dropdowns. It emphasizes the evaluation of model performance and the visualization of dimensionality reduction outcomes.
Description for Interactive ML Dashboards using Plotly Dash
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Coursera Project Network
Duration: 1.5 hours
Schedule: Hands-on learning
Pricing for Interactive ML Dashboards using Plotly Dash
Use Cases for Interactive ML Dashboards using Plotly Dash
FAQs for Interactive ML Dashboards using Plotly Dash
Reviews for Interactive ML Dashboards using Plotly Dash
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Interactive ML Dashboards using Plotly Dash
The AI tool empowers non-programmers to construct and deploy AI, featuring data transformation, insights generation, identification of critical drivers, and prediction and forecasting functionalities to enhance business decision-making and planning processes.
AI-Signals, driven by AI algorithms, offers precise trading insights including institutional concepts, automated analysis, and access to a VIP Discord community, while potential intermittent errors and subscription requirements may be considerations.
Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world
Utilize Generative AI to optimize marketing creativity. Explore the potential of Generative AI to revolutionize and influence your marketing organization.
Learn the significance, use cases, history, and pros and cons of generative AI in a business context, with a focus on its relationship to machine learning and services at Amazon.
Acquire practical skills to build a generative AI application by constructing a retrieval augmented generation (RAG) system using data, Qdrant, and LLMs.
The "Introduction to Vertex AI" course provides a four-hour, practical, and fundamental overview of Vertex AI, ideal for professionals and enthusiasts aiming to leverage AI effectively.
Investigate the field of artificial intelligence and machine learning. While investigating the transformative disciplines of artificial intelligence, machine learning, and deep learning, enhance your Python abilities.
Featured Tools
Develop and evaluate machine learning models using regression, trees, and unsupervised techniques to address various business challenges.
Learn to leverage advanced algorithms and data structures for efficient data management, algorithm development, and application performance optimization.
Besides Python programming and data science fundamentals, the course covers supervised machine learning regression, which includes training models for continuous outcomes, error metrics, Elastic Net, LASSO, Ridge regularization, and data science fundamentals for aspiring data scientists.
This course provides practical competencies in generative artificial intelligence, large language models, and natural language processing data management, all underpinned by a credential esteemed within the industry.
Learn to develop interactive web applications with Python and Streamlit, train machine learning models using scikit-learn, and visualize evaluation metrics for binary classification algorithms.