Design machine learning processes to build predictive models

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Reference no: EM133919067

Artificial Intelligence and Machine Learning in IT

Assessment - Machine Learning Demonstration

Type - Simulation and Evaluation

Task
Your second assessment requires you to complete a simulation and presentation by using Python libraries in Machine Learning. You will need to understand different types of machine learning algorithms and some commonly used Python libraries prior to building the predictive models using the supplied dataset.

Assessment Description

Python library is a collection of modules that are linked together. It has code bundles that can be used repeatedly in different programs. It makes programming easier and simpler due to the re-use attribute of a Python library.

In the previous workshops, you have learned and seen some commonly used Python libraries such as Pandas, Matplotlib, NumPy, SciKit-Learn (SK-Learn) etc. You will be given a dataset, and you need to choose two applications that you learnt to develop predictive models and explain the process in the context of machine learning algorithms as a presentation format. Get expert-level assignment help in any subject.

The learning outcomes you will demonstrate in performing this assessment includes:

LO3: Design machine learning processes to build predictive models
LO4: Create supervised and unsupervised machine learning algorithms

Assessment Instructions

Part A: Simulation of Machine Learning
Using the supplied dataset, design and run a predictive model in your own development environment. Ensure that you:
Work on Python libraries to analyse the given dataset which will enable you to assess the characteristics of data and discover findings that lead to implications.
Use the provided dataset to create a predictive model. Consider the following:
The appropriate machine learning algorithms.
The output from running the model.
Part B: Evaluation and Presentation
You are required to create a slide deck to evaluate and showcase your work from Part A, considering the following:
Use a presentation tool such as PowerPoint.
Show the applications used to assess the dataset and create the model by selected Python libraries.
The process of choosing the appropriate machine learning algorithms.
The output of the predictive model.
Other methods you could use for prediction and contrast with the one you have used.
Recommendations that you will provide based on the findings and implications.

Reference no: EM133919067

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