Data Science: ML
Learn the fundamental machine learning techniques, such as regularization, algorithms, and cross-validation, as you construct a recommendation system.
Description for Data Science: ML
Fundamentals of Machine Learning: Acquire a basic comprehension of the principles and algorithms of machine learning.
Cross-validation: Acquire the knowledge necessary to conduct cross-validation in order to prevent overtraining and guarantee the accuracy of the model.
Machine Learning Algorithms: Investigate the most prevalent machine learning algorithms employed in predictive modeling and recommendation systems.
Developing Recommendation Systems: Discover the process of creating a recommendation system that utilizes machine learning techniques and data.
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 13
Offered by: On edX
Duration: 2�4 hours per week approx 8 weeks
Schedule: Flexible
Pricing for Data Science: ML
Use Cases for Data Science: ML
FAQs for Data Science: ML
Reviews for Data Science: ML
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Data Science: ML
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.
This AI Forecast tool, powered by machine learning, offers accurate forecasts for business needs, featuring automated data processing, customizable models, and seamless integration with AWS, yet novices may find its ML-based approach challenging, and data transfer costs may apply.
This helps to integrates data from various restaurant systems, utilizes advanced analytics for decision-making, and provides real-time insights to optimize operations and profitability effortlessly.
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 to use generative AI tools to improve data science workflows, enhance datasets, and refine machine learning models through practical projects.
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.
Featured Tools
The curriculum provides students with the ability to employ search techniques and deep learning to resolve intricate AI issues in real-world scenarios.
Utilize machine learning in the supply chain. You will acquire the ability to employ machine language techniques to forecast and analyze retail stock within the supply chain.
Develop essential product development artifacts, create a personal portfolio demonstrating product management skills, and assess readiness for the AIPMM Certified Product Manager (CPM) certification exam.
Gain the skills and industry experience needed to lead successful machine learning projects and advance your career in AI.
Learn to develop, assess, and enhance machine learning models using Python libraries, covering introductory deep learning, supervised, and unsupervised learning algorithms.