ML with Apache Spark
Gain comprehensive knowledge of ML pipelines, model persistence, Spark applications, data engineering, and hands-on experience with Spark SQL and SparkML for regression, classification, and clustering.
Description for ML with Apache Spark
Features of Course
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by IBM
Duration: 15 hours (approximately)
Schedule: Flexible
Pricing for ML with Apache Spark
Use Cases for ML with Apache Spark
FAQs for ML with Apache Spark
Reviews for ML with Apache Spark
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for ML with Apache Spark
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.
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.
Learn to describe and implement various machine learning algorithms in Python, including classification and regression techniques, and evaluate their performance using appropriate metrics.
Featured Tools
In the context of machine learning, this course teaches how to use Vertex AI for monitoring and prediction, manage and preprocess data, and apply model tweaking.
Explore the functionality, practical applications, limitations, and advancements of diffusion models, including their text-to-image applications.
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.
Acquire practical business analytics expertise. Utilize data to resolve intricate business challenges.
Acquire a novel approach to learning and reasoning in intricate fields.