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
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
The course "Building a Generative AI Ready Organization" offers the necessary components for the successful adoption of Generative AI within an organization. This course concentrates on business leaders and other decision-makers who are currently or potentially involved in Generative AI initiatives.
Learn to apply image processing, analysis methods, and supervised learning techniques using Python, Pillow, and OpenCV to address computer vision issues across various industries.
Master the AI and machine learning toolkit. Mathematics for Machine Learning and Data Science is a Specialization that is accessible to beginners. In this program, you will acquire the basic mathematics tools of machine learning, including calculus, linear algebra, statistics, and probability.
The primary objective of this program is to integrate AI tools into education while addressing ethical standards in the development and implementation of AI.
Understand AI, its applications, concepts, ethical concerns, and receive expert career guidance.