ML - Anomaly Detection via PyCaret
In a nutshell, this concentration helps business professionals get ready for the CDSP exam by teaching them how to put data science knowledge to use in real-world scenarios.
Description for ML - Anomaly Detection via PyCaret
Overview of Anomaly Detection: Understand the principles and significance of anomaly detection in machine learning applications.
Configuration of PyCaret for Anomaly Detection: Configure PyCaret for anomaly detection with minimal coding necessary.
Development and Representation of Algorithms: Develop, illustrate, and evaluate diverse anomaly detection methods to accurately identify outliers.
Hands-On Project-Based Learning: Acquire hands-on experience using PyCaret's tools to construct and evaluate models effectively.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Google Cloud
Duration: 2 hours
Schedule: Hands-on learning
Pricing for ML - Anomaly Detection via PyCaret
Use Cases for ML - Anomaly Detection via PyCaret
FAQs for ML - Anomaly Detection via PyCaret
Reviews for ML - Anomaly Detection via PyCaret
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML - Anomaly Detection via PyCaret
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.
Legaliser is an AI-powered platform facilitating contract analysis and drafting for personal and business needs, featuring contract evaluation, fairness assessment, risk analysis, and anomaly identification.
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.
Use AI skills to advance your engineering career. Acquire practical knowledge regarding deep learning methodologies for computer vision.
Featured Tools
Learn to use Generative AI for creating compelling logos and establishing a strong brand identity that fosters customer loyalty.
Master Generative AI to improve productivity, automate tasks, and enhance creativity in real-world applications. Develop practical skills, from foundational knowledge to advanced prompt engineering.
Create a final presentation to evaluate peer projects, train neural networks for regression and classification, and develop Python-based recommender systems. Additionally, employ KNN, PCA, and collaborative filtering.
In order to facilitate effective learning, this course provides learners with the necessary skills to develop scalable and resilient ML solutions on AWS, combining theory and practical experience.
Unlock and capitalize on the capabilities of generative AI. Discover how the capabilities of generative AI can be leveraged to improve your work and personal life.