Description for Scalable ML on Big Data using Apache Spark
Features of the Course:
Practical Application of Apache Spark: Acquire a comprehensive comprehension of Apache Spark to effectively resolve machine learning challenges, including the seamless management of large datasets.
Efficient Parallel Computing: Acquire the ability to compose parallel code that is capable of operating efficiently on thousands of CPUs and eliminates out-of-memory errors that are frequently encountered in conventional machine learning frameworks.
Scalable Machine Learning with SparkML Pipelines: Employ Apache SparkML Pipelines to execute machine learning algorithms on petabytes of data and evaluate thousands of models in parallel to ensure optimal performance.
Optional Advanced Features: Examine the potential of performing SQL queries on extensive datasets using the Spark DataFrame API and Apache SparkSQL to gain additional functionality.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 22
Offered by: On Coursera provided by IBM
Duration: 6 hours at your own pace
Schedule: Flexible
Pricing for Scalable ML on Big Data using Apache Spark
Use Cases for Scalable ML on Big Data using Apache Spark
FAQs for Scalable ML on Big Data using Apache Spark
Reviews for Scalable ML on Big Data using Apache Spark
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Scalable ML on Big Data using 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.
NovaceneAI streamlines the organization of unstructured text data with AI algorithms, offering dedicated cloud hosting, adaptability across sectors, and robust data privacy measures.
Posit offers a comprehensive platform with enterprise solutions, cloud applications, community resources, and deployment solutions to enhance productivity in data science teams.
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.
Develop generative AI capabilities for data analytics. Learn about generative AI to advance your career as a data analyst! No prior experience is required.
Achieve a professional status as an AI Engineer. Acquire the knowledge necessary to develop next-generation applications that are propelled by generative AI, a skill that is indispensable for startups, agencies, and large corporations.
Enhance your Product Manager career with Gen AI. Boost your Product Manager career in under two months by developing hands-on, in-demand generative AI skills. No prior experience is required to initiate the process.
Delve into the historical evolution of Generative AI and AI, exploring diverse models and their applications in business contexts for optimized decision-making and innovation.
Begin your vocation in generative AI data engineering. Obtain the necessary skills to secure a position as a data engineer by acquiring an understanding of generative AI. No prior experience is required.
Explore the evolution and business implications of generative AI, emphasizing data significance, governance, transparency, and practical applications in modernization and customer service in this course.
Featured Tools
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.
This course covers the development, impact, and future of Generative AI through lectures, critical AI technologies, and interactive assessments.
This beginner's course covers the fundamentals of Python programming, including essential abilities such as functions, loops, and variable utilization.
The Specialization emphasizes the development of practical applications, such as encryption, geospatial maps, CSV data analysis, and text data management, through the use of object-oriented design and advanced Java programming. This includes the ability to handle large datasets and create GUI programming.
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world