Machine learning or AI is a field of software engineering that utilizes different factual methods to let the PC learn all alone by breaking down the information without programming. Machine learning is for the most part utilized in Artificial Intelligence. AI significantly centers around creating PC applications that can get to information and utilize this information to learn without human mediation. The learning procedure begins by watching or with the assistance of information. The primary point is to let PC adapt consequently without the help of people.
Machine learning or AI will utilize calculations that will get information as an info and utilize factual methods to envision the yield while continuing refreshing the yield with the adjustment in the information. The procedure that is utilized in AI is similar to that is information mining and prescient models. In both these procedures, scan the information for design and as needs be alter the program activities. This causes the organizations to make the right business choices by investigating enormous tosses of information. There are various fields that are utilizing AI.
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Classification techniques:
Algorithms used to perform classification include:
Regression technique :
The key regression algorithm techniques that are used include:
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The following techniques are used to explain the data. These include:
Clustering: This is used to carry out exploratory data analysis to find out hidden patterns or data groups. The key applications where this type of technique is used include market research, object recognition, etc.
Dimensionality reduction:
This algorithm will stand between supervised learning and unsupervised learning. This type of learning will pick a few aspects in each of these learning and form into one. This uses labeled and unlabeled data for carrying out training. Enhance your understanding of the subject by availing Machine learning homework help from our experts.
The key reinforcement machine learning includes:
Synopsis of the task and its context
This is an individual assignment making up 20% of the overall unit assessment. The assessment criteria for this task are: 1) Apply machine learning pipeline to solve a real-world problem.
Match between learning outcomes and criteria for the task:
Description
In this assignment, we will apply machine learning techniques learned in the lectures and tutorials to predict the highest price of a stock in the next day.
In this task, you will train an AI model using the open price, the low price, and the volume of a day to predict the high price on the next day. In this task you need to design a RapidMiner process OR Python program to:
DON’T NORMALISE THE TARGET (LABEL) ATTRIBUTE.
When you complete the step 8, you will do stage-1 submission in week 13 (see below) to score the performance of your model.
You will receive the performance score after week 13 and the ground truths. You will need to revise your design to:
Appendix 01: How to export an XML file for the model with RapidMiner
Appendix 02: How to export a csv file for the predicted output using RapidMiner
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