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Machine Learning Startup Idea

Possible Machine Learning Startup Ideas

Machine Learning is going to prove a very powerful solution to some big problems which public is facing. This is possible because of making machine learn about situations in real world. This is something which everybody face.

We came with following 2 powerful ideas for you which can be thought over.

1. News Predictor

In this, you can make an application which continuously takes recent news as data. Then divide the data containing following sections at least. Then, try to come up with a mobile application, website or software.

1. Area

News Area

Source

You can divide into continents, countries, states, districts, cities, etc. Try to narrow down as much as possible.

2. Date and Time

Date and Time

Entries in this section will help ML application to predict how frequently a news occur based on area. So, the result will help to find that this particular area can generate news in a particular date and time.

3. Type of People Involved

You can further divide this into Age, Age groups, Occupations, Family Background, Marital status, number of children involved and other demographic factors.
This will help ML application to find the overall behavior of different sections of people  and their upcoming actions. Therefore Government can plan actions accordingly.

4. Involvement/Action of Politicians

Politician

This section can either be dependent or independent.
So, you can include this factor as new sub-column. Further possible sub-column can be their personal and their party information, speech location, purpose of speech, actions done by their party members, losses and gains caused by politicians and their parties.
Hence, this will help Machine Learning to understand general and specific behavior of some specific politicians. So, using this information, politicians will be cautioned in their actions.

5. Terrorist Information

Terrorist

Sub-sections lying under this can be their location of attack, number of people injured and died, number of terrorists identified, number of terrorists killed, number of terrorists survived, etc.
This data will help ML application to predict their future plan of attack and forecast it to authorities before any similar incident occurs again.

6. Crime information

Crime Scene

Sub-sections lying under this can be crime location, person or people involved, their demographic information, date and time of crime, people injured or killed, loss of property and money, etc.

7. Other possible events

Columns lying under this depends upon the nature of incident and factors involved in it.
Benefits -:

1. Government

It can use this information to plan their actions in advanced in favor of country. Also Government can anticipate their securities against terrorist attacks based on their pattern of attack.

2. Public

They will get quality news whose information can be useful to them. So, public can plan their routines and future plans based on upcoming changes in their country, state, district, city, etc.

3. Politicians

They will become more alert and cautious as their behavior will start to be predicted using ML. Therefore, based on learning ability of ML, it will give very accurate information about their future actions.
So politicians will strongly hesitate to do anything which causes problems to public and give them profits.

4. Police

Police, after checking this data can plan in advance the security measures to arrest and stop criminals based on their pattern of theft.

2. Court case Predictor

Similar to News Predictor, you can design an application which accepts court case files as big data. The application analysis the data and then predicts the type of cases, people, matter, disputes, charges, conviction which can come in future time.

Your application can work finely if your data has at least following sections -:

1. Types of Cases

This section can have data like Criminal Case, Civil Case, Bail Applications, Family law cases, etc. So, this can help ML Applications to find out which type of cases can come up either frequently or in large number.

2. Types of People

Types of People

Source

This section can have demography of people involved in a case. For example cases involving children, youths, middle-aged, old person etc. Using this, ML can understand the strength of offense involved in the case.

3. Charges accused

Charges Accused

Source

This section can be descriptive in nature as it involves detailed explanation of scenes created by the parties involved. Since it can have a wide variety, so it becomes big data itself.

Therefore dividing this section into sub-sections where each sub-section is associated with each party will help perform the application better.

Then combine these two sections and associate it with winning party. So, ML application can have information on details of scenes created by each party and party which has won. This will help application to decide what is right and what is wrong.

4. Time taken to Complete The Case

This section deals with time taken between filing a case and coming to final decision by judge leading to close the case. This section can be associated with Charges Accused section. This will help application not only to know what is wrong and right, but time taken to find this out.

For You: 6 Interesting Machine Learning Project Ideas for Beginners

Benefits -:

1. Enabling Application to Judge

If Machine Learning model has sufficient accuracy, then each court can gain trust over it. This is because, the application takes decision based on data and knowledge. On doing correct calculations and making decisions, ML can say, which party needs justice.

This decisions and calculations will be based on offenses, scenarios made by each party.

2. Judgement Speed will be Faster

Since, machine can learn faster than human, so this is possible. This solves one of the greatest public pains i.e. waiting for years for court to make decisions. This makes life of involved people miserable by regularly attending courts, police stations, etc.

The main reason is that your application can work 24 hour on one case unlike human.

3. Judgement will be Accurate

This is possible because judgement will be data driven. This can further help to reduce the time of hearings. Because at one hearing, the application will give as much conclusions and decisions as possible. This will improve the satisfaction and clarity to the parties regarding the case.

4. Reduced cost for Public

For winning a court case, advocates and lawyers plays vital role. But charges taken by them is in range from ten thousands to several lakhs. Involving applications to accept the case will be cheaper as keeping and interpreting data can become automatic.

5. Reduced number of hearings

Because of reduced time of decision making, number of hearings will automatically reduce. This is because number of hearings for one case increase because of more time taken by cases in queue. Also increased accuracy of conclusion in one hearing can further reduce it.

Finally, if above two ideas are considered with a powerful business model, then this can create a revolutionary impact.

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