Description for ML con Spark (MLlib) en Databricks
Level: Advanced
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Coursera Project Network
Duration: 2 hours
Schedule: Hands-on learning
Pricing for ML con Spark (MLlib) en Databricks
Use Cases for ML con Spark (MLlib) en Databricks
FAQs for ML con Spark (MLlib) en Databricks
Reviews for ML con Spark (MLlib) en Databricks
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML con Spark (MLlib) en Databricks
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.
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.
Master the operations of large language models. Acquire proficiency in the deployment, management, and optimization of extensive language models on a variety of platforms, such as Azure, AWS, Databricks, local infrastructure, and open source solutions, through practical projects.
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
Acquire a thorough comprehension of the significance of ethics in the development of AI systems, as well as AI technologies, including generative AI.
Leverage Python programming skills to develop and analyze comprehensive clustering procedures, thereby mastering the fundamental concepts and operations of data clustering, with a particular emphasis on the K-means algorithm.
Learn to develop, assess, and enhance machine learning models using Python libraries, covering introductory deep learning, supervised, and unsupervised learning algorithms.
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.
Learn to clean, prepare, analyze, and manipulate data with Python, utilize libraries for exploratory data analysis, and develop regression models for prediction and decision-making using scikit-learn.