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I have set of transactions from a retail store. If I need to cluster the customers based on buying pattern I can do that using K-Means algorithm in Python.
How can I predict based on their earlier buying pattern, what are all products customers would be interested to buy in coming months?
I need to list products based on their choice of buying preference (high to low). What models or algorithm can be used for this?
Association Analysis is a text-book algorithm build for this use-case. You can also use Collaborative Filtering can also be used to model the problem that you've described.
Here is a Python implementation of Apriori Algorithm which I believe would help you
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For a course term project we have to build a machine learning algorithm in which user fills the form and the algorithm analyse the best suitable university based on the responses. I am new in the field of machine learning and I do not know what kind of algorithm can we use. Is the recommendation systems a right approach for this?
I did some review on the internet for some similar projects, however still can not find a good resource.
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I have a dataset that has, users, items and views,which is the interaction between user and item.
The only difference in this dataset from the other recommendation datasets is that, the items have strong timeliness i.e. the items expires after a certain time period and won't be considered anymore.(Items life span can range from 1 week - 4 months)
You can use Bayesian Personalized Ranking for implicit feedback. I wrote about my experience of building such recommendation systems using Tensorflow.
Regarding timeliness, you should use only active items to find recommendations.
For an example of the workflow can look like:
you need to recommend 5 items;
you ask the system to give you 30 recommendations using only active items;
then exclude items that will expire in the next 2 days;
then randomly select 5 from those who stayed;
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I am looking for the machine learning correct approach for predicting the lottery numbers, not the most accurate answer but at least we have some predicted output. I am implementing the regression based and neural network models for this. Is their any specific approach which follows this?
It is impossible. The lottery numbers are random - actually to be more specific, the system is chaotic. You would require the initial configuration (positions etc) to insane (possibly infinite) precision to be able to make any predictions. Basically, don't even try it.
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I have a paragraph, system has to understand it and it should answer all the questions asked by the user. Please name the techniques and methodologies.
It all depends on the problem that you are trying to solve, the data available to you and the underlying domain. Lets get to it one by one:
Type of Problem
There are multiple types of question answering systems, like one word answers based on extract the exact answer from various sentences, or returning the most similar sentence from a list of sentences based on the question asked by the user, using various similarity and embedding techniques. I think this paper : Teaching Machines to Read and Comprehend should be a good place to start getting an idea about such systems.
Dataset
Next comes the dataset for such systems. Now there are various datasets available for question answering systems like :
SQuAD dataset
QA dataset based on Wikipedia Articles
Facebook bAbI dataset
AllenAI dataset based elementary Science question
NewsQA datset
Methodologies
Well there are multiple ways to go about solving this problem. It would be difficult to list all of them in one answer, but I can provide you some references:
Deep Learning for Question Answering
Various Deep Learning models on Question answering
SquAD dataset Leaderboard
Question Answering based on Word Alignment
Attention Based Question Answering
Reasoning-based QA
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Hi i want to predict health level(High,medium,low) in leaf using image processing and data mining.So far i thought using extract colors from leaf using Bayes algorithm to predict healthy of leaf. and data mining part have completed now.but i need extra features for prediction.we only used orchid leaf.So i can't use vain structure.Can anyone help me to what are the other features can be extracted from leaf for identify health level of leaf.Any idea or comments help me to improve my project. Thanks
There are many possible approaches to a problem like this. One common method is the bag-of-features model. Take a look at this example using the Computer Vision System Toolbox in MATLAB.