How to solve a problem using Machine Learning? Steps in Machine Learning Explained

How to solve a problem using Machine Learning? Steps in Machine Learning Explained

Hi Guys In this Article we are going to see a complete insight on  How to apply a Machine Learning algorithm to solve the problem or to give solution for the process These upcoming five steps will help you in doing this Describe your problem, Collect and analyze data,  Verify algorithms, Optimize your results, Demonstrate your results Having seen the glimpse of few steps in this,  we will be going on to the complete explanation with an example.

How it will be actually helping in solving the problem using Machine Learning The first step is describe your problem To describe your problem, you have to ask yourselves these questions to give an answer What is the problem? Why do you want to solve the problem?  And how do you think you can actually solve the problem? Let me give you a simple example related to a business strategy One of my friend who is running a hotel business actually seeing a complete downfall in this. So this will be giving the answer for what is my problem Next thing is why do you want to solve this problem? Because my friend is actually facing a complete downfall in his business  and he cannot able to find the solution for it.

The next question comes to your mind is How do you think you can actually solve this problem? You can solve this problem by collecting and analyzing  the offline and the online data and the reviews available through a structured process using a Machine Learning Algorithm.

The next step is collect and analyze data In this step, you need to collect the related information to solve the problem In this hotel business, what are all the related data I should be collecting? The data regarding the reviews which is given in the online And then the comments which is given by the words in the offline  and then the availability of swimming pool, its complete rent during the weekdays, weekends and then the complete transport availability from the nearest airport and then the nearest public views which will be helpful for me in complete analyzing and giving the solution for this problem by feeding this data into an algorithm After the data collection, you need to organize your data  by selecting, deleting and then adding the related information if you need Depending upon the availability of the data, you can actually do the data processing steps.

If the available data is less, you can collect the incomplete data  And if you want to remove any data, you can actually remove it And if you think that it is not formatted well, you can actually format it. Upon collecting these data, if you feel that the data amount the dataset you have collected is very much large,  you can actually select the samples from it and can utilize it  to reduce the minimum utilization of the machine  and then you can actually reduce the running algorithms  so that it will be helpful in giving the precise output at the precise time.

Upon collecting the data for this hotel business,  I found that some of the fares during the festive season  and then the particular time have been actually been missed out So that this step has been helpful in adding those data into the system After these steps, you need to actually transform the data  according to your purposes to make the problem statement minimized and then to work on it effectively

The first step is by scaling For example, the reviews which have been given in online has been given at the rating of 1 to 5 so that everything has converted into these formats And then the next thing is availability of wifi, swimming pool have been denoted by 0s and 1s so that it will be helpful in calculating the precise output based on the algorithm working function Next thing is by decomposing In this step, I actually splitted the rents  based on the weekdays, weekends, festive seasons and then the special occasions.

This helpful in giving the detailed analysis whichever part you considered as more important The next step is by aggregating In this step, you can actually combine the data of various things  like availability of the swimming pool, wifi and then the some other small factors which you find not important for it  so that it will be helpful in solving the problem easily and then the time consumption for the algorithm step can also be reduced.

The third process is verifying the algorithm Yes, you heard it right You need to verify your algorithms to find  if it is working better to give the accurate and then the needed results. You can use 10 to 20 algorithms depending upon your domain knowledge and then the time availability to experiment and verify your testing on your processed and then the transformed data  The main reason to verify the algorithms then and there is to identify the types of algorithms and then the dataset combination that can work better in bringing the structure to the problems.

For this hotel business example,  I actually verified the algorithm to find the distance between the public transport and then the availability of the hotel so that it will be helpful in giving the accurate result at the end of the process One of the best algorithm which will be helpful in solving your problem  during the verifying the algorithm step is spot check algorithm It will give you a precise output then and there so that you can actually analyze whether to proceed to the next step  or you need to process the current step to give the better output at the end of the result.

So that the verifying the algorithm step is a major part  and it will be helpful in solving the errors which is occurring at the last  so that you can make it easily and simply at the end of the result to avoid this problem The number four processing step is optimizing your results. Whenever you process and got the final result,  you need to actually recheck your algorithm to get the optimized output at the end of the results.

As you know that, there is always room for improvisation in this ever changing kaizen world So, how you can actually improvise?  In this you can actually improvise by scaling and then aggregating  and then by decomposing some of the steps in the complete processes  and you can actually mix up 2 or 3 algorithms in a particular step  so that the processing time and then producing the accuracy at the end can also be improved After completion of these steps in analyzing the hotel business in this step what improvisation I have done is when doing the complete analysis I found that there is always a craze for booking the hotels during the New Year Eve So that I actually helped the customer to find this  and he can actually put lot of things like promotions during that time to attract more users for his hotel.

The next and the final step in this process is demonstrating your results. Whenever you got the final result, you need to actually demonstrate it  to the end user or your customer in a precise way to make it understandable so that it will actually help in improving their businesses.

These preparation of the results not only help in attracting the end users or the customers it will actually help you to improvise your steps  in the next upcoming algorithms so that you can give more precise output than this So guys, I think you have got the complete insight of  how the machine learning process actually works So that put this in your steps in your businesses in solving your problems  so that let’s see how it will be helpful for you.

About: AbbasSheikh