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Bike Rental Sharing Demand Prediction with Machine Learning
Ryan Ahmed
Ryan Ahmed
In this 1-hour long project-based course, you will learn how to predict bike sharing demand with machine learning. Bike sharing services enable people to rent a bike from one location and drop it off at another location on an as-needed basis. The objective of...
Read more
In this 1-hour long project-based course, you will learn how to predict bike sharing demand with machine learning. Bike sharing services enable people to rent a bike from one location and drop it off at another location on an as-needed basis. The objective of...
Read more
In this 1-hour long project-based course, you will learn how to predict bike sharing demand with machine learning. Bike sharing services enable people to rent a bike from one location and drop it off at another location on an as-needed basis. The objective of this guided project is to predict bike sharing rental usage based on inputs such as temperature, season, humidity, wind speed.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/z21frb/bike
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches bike sharing demand prediction techniques with machine learning
Uses bike sharing data to build predictive models
Provides hands-on experience with bike sharing demand prediction
Suitable for beginners with no prior experience in machine learning
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Bike Rental Sharing Demand Prediction with Machine Learning with these
activities:
Learn to use Python libraries
Show steps
Understanding the fundamentals of Python and these key libraries will ensure you will be able to make the most out of the course content and avoid getting stuck on what should be relatively minor issues.
Browse courses on
Python
Show steps
-
Find tutorials on pandas
-
Complete the pandas tutorial
-
Find tutorials on numpy
-
Complete the numpy tutorial
Practice with bike sharing data
Show steps
Practice loading and cleaning bike sharing data will help you quickly familiarize yourself with how it looks and what it covers.
Browse courses on
Machine Learning
Show steps
-
Download the bike sharing data
-
Load the data into Python
-
Clean the data
-
Save the results
Discuss the course with your peers
Show steps
Exchanging insights with peers can help you reinforce concepts, identify areas for improvement, and get different perspectives on the course material.
Show steps
-
Find a study partner or group
-
Schedule regular meetings
-
Discuss the course material
-
Work on practice problems together
Two other activities
Expand to see all activities and additional details
Show all five activities
Create a simple machine learning model
Show steps
Create a basic model to predict bike sharing demand. This will help you understand the general idea of machine learning and its application in this context.
Browse courses on
Machine Learning
Show steps
-
Import the necessary libraries
-
Load and clean the data
-
Create a simple model
-
Train the model
-
Evaluate the model
-
Save the model
Contribute to an open-source project
Show steps
Contributing to an open-source project will expose you to real-world machine learning applications and help you develop practical skills.
Browse courses on
Machine Learning
Show steps
-
Find an open-source project to contribute to
-
Read the project documentation
-
Identify an area where you can contribute
-
Code your contribution
-
Submit a pull request
Learn to use Python libraries
Show steps
Understanding the fundamentals of Python and these key libraries will ensure you will be able to make the most out of the course content and avoid getting stuck on what should be relatively minor issues.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find tutorials on pandas
- Complete the pandas tutorial
- Find tutorials on numpy
- Complete the numpy tutorial
Practice with bike sharing data
Show steps
Practice loading and cleaning bike sharing data will help you quickly familiarize yourself with how it looks and what it covers.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Download the bike sharing data
- Load the data into Python
- Clean the data
- Save the results
Discuss the course with your peers
Show steps
Exchanging insights with peers can help you reinforce concepts, identify areas for improvement, and get different perspectives on the course material.
Show steps
Show steps
Show steps
- Find a study partner or group
- Schedule regular meetings
- Discuss the course material
- Work on practice problems together
Two other activities
Expand to see all activities and additional details
Show all five activities
Create a simple machine learning model
Show steps
Create a basic model to predict bike sharing demand. This will help you understand the general idea of machine learning and its application in this context.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Import the necessary libraries
- Load and clean the data
- Create a simple model
- Train the model
- Evaluate the model
- Save the model
Contribute to an open-source project
Show steps
Contributing to an open-source project will expose you to real-world machine learning applications and help you develop practical skills.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find an open-source project to contribute to
- Read the project documentation
- Identify an area where you can contribute
- Code your contribution
- Submit a pull request
Career center
Learners who complete Bike Rental Sharing Demand Prediction with Machine Learning will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and deploys machine learning models to solve real-world problems. This course can help aspiring Machine Learning Engineers build the skills they need to develop models that can predict bike sharing demand. The course covers topics such as data preprocessing, feature engineering, and model evaluation, which are essential for success in this field.
Data Scientist
Data Scientist
A Data Scientist uses data to solve complex problems and make predictions. This course can help aspiring Data Scientists develop the skills they need to build models that can predict bike sharing demand. The course covers topics such as machine learning, statistical modeling, and data visualization, which are essential for success in this field.
Data Analyst
Data Analyst
A Data Analyst gathers, cleans, and interprets data to identify trends and patterns. This course can help build a foundation for a career as a Data Analyst by providing learners with the skills to predict demand for bike rentals using machine learning. This course can be particularly useful for Data Analysts who want to specialize in the transportation industry.
Transportation Planner
Transportation Planner
A Transportation Planner designs and implements transportation systems to meet the needs of a community. This course can help Transportation Planners understand how to use data to predict demand for bike sharing services. This knowledge can be used to plan and design bike sharing systems that are efficient and meet the needs of the community.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and analytical techniques to solve complex problems in a variety of industries. This course can help Operations Research Analysts develop the skills they need to apply machine learning to solve problems in the transportation industry. The course covers topics such as optimization and simulation, which are essential for success in this field.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data to provide insights for businesses and organizations. This course can help aspiring Statisticians develop the skills they need to understand data, develop statistical models, and communicate their findings. The course covers topics such as probability, statistical inference, and regression analysis, which are essential for success in this field.
Business Analyst
Business Analyst
A Business Analyst gathers and analyzes data to identify opportunities and solve problems for businesses. This course can help Business Analysts develop the skills they need to use data to make better decisions. The course covers topics such as data visualization and statistical analysis, which are essential for success in this field.
Marketing Manager
Marketing Manager
A Marketing Manager is responsible for developing and executing marketing campaigns to promote products and services. This course can help aspiring Marketing Managers develop the skills they need to understand their target audience and develop marketing campaigns that are effective and reach the right people.
Academic Researcher
Academic Researcher
An Academic Researcher conducts research in a variety of fields. This course can help aspiring Academic Researchers develop the skills they need to design and conduct research studies, analyze data, and write research papers. The course covers topics such as research methods, data analysis, and scientific writing, which are essential for success in this field.
Sales Manager
Sales Manager
A Sales Manager is responsible for leading and motivating a sales team to achieve sales targets. This course can help aspiring Sales Managers develop the skills they need to understand their customers and develop sales strategies that are effective and close deals.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course can help aspiring Software Engineers develop the skills they need to build software applications that can predict bike sharing demand. The course covers topics such as object-oriented programming, data structures, and algorithms, which are essential for success in this field.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data to make investment recommendations. This course can help aspiring Financial Analysts develop the skills they need to understand financial data and make sound investment decisions. The course covers topics such as financial modeling, valuation, and risk management, which are essential for success in this field.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products. This course can help aspiring Product Managers develop the skills they need to understand the needs of their customers and develop products that meet those needs. The course covers topics such as market research, user experience design, and product development, which are essential for success in this field.
Consultant
Consultant
A Consultant provides advice and guidance to businesses on a variety of topics. This course can help aspiring Consultants develop the skills they need to understand the needs of their clients and develop solutions that meet those needs. The course covers topics such as problem-solving, communication, and project management, which are essential for success in this field.
Entrepreneur
Entrepreneur
An Entrepreneur starts and runs their own business. This course can help aspiring Entrepreneurs develop the skills they need to identify opportunities, develop business plans, and launch their own businesses. The course covers topics such as market research, customer development, and financial planning, which are essential for success in this field.
For more career information including salaries, visit:
OpenCourser.com/course/z21frb/bike
Reading list
We've selected 11 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Bike Rental Sharing Demand Prediction with Machine Learning.
Save
Provides a comprehensive guide to deep learning. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive guide to machine learning and statistical modeling. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive guide to statistical learning. It covers topics such as supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive guide to machine learning using Python. It covers a wide range of topics, including supervised and unsupervised learning, feature engineering, and model evaluation.
Provides an introduction to reinforcement learning. It covers topics such as Markov decision processes, value functions, and policy gradients.
Provides a comprehensive guide to the mathematics of machine learning. It covers topics such as linear algebra, calculus, and optimization.
Provides a probabilistic perspective on machine learning. It covers topics such as Bayesian inference, graphical models, and reinforcement learning.
Save
Provides a comprehensive guide to time series analysis. It covers topics such as stationarity, seasonality, and forecasting.
Provides a comprehensive guide to Bayesian data analysis. It covers topics such as Bayesian inference, Markov chain Monte Carlo, and hierarchical models.
Save
Provides a comprehensive guide to the mathematics of machine learning. It covers topics such as linear algebra, calculus, and optimization.
Provides a practical guide to data science for business professionals. It covers topics such as data mining, data visualization, and predictive analytics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/z21frb/bike
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Good to know
Teaches bike sharing demand prediction techniques with machine learning
Uses bike sharing data to build predictive models
Provides hands-on experience with bike sharing demand prediction
Suitable for beginners with no prior experience in machine learning
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