AI and ML - Creating, training and a model using python in jupyter notebook
Budget $10-30 USD
Job Description:
Jupyter Notebook Contents
The various sections in the notebook should include code, code comments and appropriate
Markup cells describing your approach chosen.
In detail, sections should include the following:
Introduction and Problem Definition
- Textual description providing an overview over the data
- A discussion on why this problem is a regression problem
- A detailed problem statement question as discussed in Lecture 3.
Data Ingestion
- Code to load the data into a suitable format to be used in the notebook
- A description of the statistical data types for each field in the file [login to view URL]
Data Preparation
You should assume that exploratory data analysis has taken place and the following was
concluded:
- Missing values are in the ‘temp’ and ‘atemp’ columns.
- The peak usage hours are: 7-9AM and 4-7PM on working days, and 10am-4pm on
non-working days.
- At night (10pm-4am) the bike rentals are low
- If the humidity or wind-speed is high, the number of rentals decreases.
Your data preparation steps should therefore include the following:
- Fill the missing values in the temperature columns automatically with values that
would most closely mirror the actual temperature.
- Create a new field that indicates whether it is a peak time or not
- Create a new field that indicates whether it is night time or not
- Remove all fields containing information about specific dates (‘yr’, ‘mnth’, ‘dteday’),
‘casual’ and ‘registered’ and any other variables that you deem irrelevant.
- A justification (and potential application) of whether you should use data binning or
not
- Suitable encoding of the data
Data Segregation
- Code and justification for the selection and application of a suitable data split
Model Training
- Selection of two different Regression models and justification why they are suitable.
Only one of those models should be Tree-Based (e.g. Random Forest or Decision
Tree)
- Application of those models as a baseline on the data
4
- Utilisation of manual or automatic hyperparameter optimization and justification of
your choices to create “optimized” versions of each regression model
Model Evaluation
- Selection of appropriate regression metrics and a written outline why they are
suitable for this data
- A comparison of the baseline models to the “optimized” versions and an evaluation
of the results
Conclusion
- A conclusion and interpretation of the results and suggestion of potential
improvement
13 freelances font une offre moyenne de 43 $ pour ce travail
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Hello, I read your description carefully. I am a ML / AI engineer with rich experience, and I have developed so many computer vision and machine learning projects before such as Face Detection and Recognition, Object Plus
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AI and ML - Creating, training and a model using python in jupyter notebook Good morning , Hi I am a very experienced statistician, data scientist and academic writer. I have completed several PhD level thesis project Plus
I read your description carefully and I can do this project at the top level. But I want you to increase budget a bit more. Python and Jupiter notebook are my first skills. Look at my reviews. Although I'm first on thi Plus
Hi, I am interested to work on this project, I believe I am the best freelancer to work on this project given my skill sets. I am available to start working immediately. Kindly send me a message to discuss more. Thanks Plus
Hello, I have delivered similar data using Jupyter Notebook , Pyspark and Pandas. I therefore believe I can deliver well on the assignment. Please reach out for further discussion Thank you.
I had experience in Machine Learning models I have done some projects on machine learning like house price prediction, Mask detection I can do your work excellently if you are interested to move forward lets meet in ch Plus
I am currently serving as part time AI ENGINEER at a US based company (remotely). I have graduated from renowned university NED University of Engineering and technology with Bachelor’s degree in Computer and Informati Plus
