Artificial intelligence mini projects ideas in python

Artificial intelligence

"The human race started from the invention of the wheel", and today we are about to advance to the Industrial level 4.0, where machines can work, talk, think and act like humans. But at last human brain is superior to those; artificial intelligence creates the way to evolve in these inventions and discoveries.

Artificial intelligence (AI) is the ability of a machine or computer system to simulate human intelligence or thinking processes to carry out tasks that a person would normally perform.

Artificial intelligence has a wide range of applications. It can be used in many sectors for advancement like healthcare, banking and financing, gaming, education, agriculture, entertainment, social media, robotics, and building E-commerce websites.

If you want to invest in artificial intelligence, this article would be the perfect fit for you. In this article, you will get some basic projects, which can be done using artificial intelligence. These projects will be an add-on advantage to your knowledge.

Project ideas to try

Some basic project ideas that can be done using artificial intelligence are as follows:

1. Recommendation systems

• Recommendation systems have become one of the important fields in artificial intelligence and machine learning.
• Popular streaming apps and web applications like Spotify, Netflix, and Amazon fetch a lot in this field for improving customer product recommendations.
• One can try implementing different algorithms for recommendation systems.
• The algorithms which can be used can be divided into two types,
• Content-Based Filtering.
• Collaborative Filtering.
  Content-based filtering generates the item similarity, what the user may like based on the previous data.

• Collaborative filtering filters the items based on other users who are like them and generates the model.
• Some algorithms that can be used in these projects are Cosine Similarity, KNN, neural networks.

2. Face recognition applications

• Face Recognition has a wide range of applications, and it involves verifying different people's identities.
• It can be used to identify photos; videos, and the best real-time example is the face lock application on mobile devices.
• Face Recognition can be used in attendance systems, analyzing criminal cases, smart advertising, and disease diagnosis.
• Present models on Face Recognition sometimes fail in identifying people from different regions, and it sometimes may fail in identifying the person's movements.
• Improving the already existing Face Recognition models and proposing new models can bring a profound change in different sectors.

3. Disease predictions

• Artificial Intelligence has its unique mark in the medical field, and it can be used in pharmaceutical experiments and medical diagnoses of diseases.
• Every year millions of people die due to a variety of diseases. Predicting the diseases at an early stage can reduce deaths.
• Artificial Intelligence and Machine Learning algorithms can become one of the major parts of developing the predicting models.
• These models include heart disease prediction, diabetes prediction, Tuberculosis, Dengue, Jaundice, and Malaria.

4.   Plagiarism analyzer

• Plagiarism has become the most common word in today's revolution.
• Nowadays wide increase in usage of the internet has become the major reason behind plagiarism.
• Duplication of data or content has become common, and it's hard to find whether the data or the content is plagiarized or not.
• For example, People write blogs regarding some topics; they want to know whether their work has been stolen by someone else or not.
• In these cases, a plagiarism check plays a key role in declaring whether the content or data is plagiarized or not.
• Artificial intelligence has the upper hand in building these kinds of applications.
• If you are new to artificial intelligence and a beginner, then this project aptly suits you.

5.   Stock market trading

• The stock market nowadays has become a side hustle for many people.
• Investing in the stock market has a high risk of failure. It requires the estimation of trade, rise in stocks, decline in prices and many more parameters.
• Developing a predictable model using the previous trading analytics can help to understand the ups and downs in the stock market.
• Machine learning plays a key role in developing these kinds of models.
• Apart from these models, building a model on the stock market prediction will require different strategies.

Different kinds of projects for beginners

Resume parser

• Recruiters, at the time of recruitment, invest a lot in an application or resume screening to find out a strong hire for their company.
• Resume screening plays a key role in candidate selection. Finding out a perfect or strong fit among hundreds and thousands of applicants is difficult.
• Resumes are shortlisted and screened by the recruiters based on a set of keywords, but this screening process has drawbacks; applicants are aware of these keyword matching algorithms, and if this happens, then there might be a high probability of false screening.
• With the help of artificial intelligence and machine learning, one can build a Resume Parser and filter out the resumes with unnecessary keywords and select the candidates with identified skill sets.

Fake news detection

• Spreading and circulation of fake news over the internet have become the main cause behind the spreading of rumors.
• When there are elections or pandemics, the spread of fake news is especially dangerous. People and society are at risk from false rumors and information that could endanger human lives.
• Spotting fake news and stopping it can stop it from spreading and causing panic among the population.
• You can take the data set from Kaggle to build a fake news detector.

Instagram spam detection

• Many people are fond of using Instagram these days, and the number of users is being increased every day.
• With the increase in users, increase of spam messages are also being increased.
• Some other time, you might come across comments to your post, and when you open in excitement, you come across promotions of products.
• Instagram comment section is filled with bots that generate messages ranging from annoying to dangerous, depending on the type of call to action they require from you.
• You can try to build an Instagram Spam Detector to differentiate spam messages.

Object detection system

• Object detection is a part of computer vision technology which helps in identifying and locating things in an image or a video.
• To be more precise, object detection creates bounding boxes around the items it has found, allowing us to determine their location inside (or how they move across) a scene.
• Object detection should not be confused with image recognition, image recognition only labels the image whereas object detection involves labelling through each object present in the image or video.
• Advantages of object detection.

1. Face detection.
2. Crowd counting.
3. Anomaly detection.
4. Video surveillance
5. Self-driving cars.

Handwritten digit recognition

• The handwritten digit recognition makes the computers able to understand the digits written by humans.
• Humans have different styles of writing numbers; it is hard for a machine to classify and identify the digit written in different styles.
• Handwritten digit recognition can act as a solution for this problem and make the machine understand the human handwritten digits.
• This can be done using neural networks
• Applications for digit recognition include filling out forms, processing bank checks, and sorting mail. The key challenge we come across while working with this problem is the capacity to create an effective algorithm that can recognize handwritten numbers given by users via a scanner, tablet, and other digital devices.

These are the basic and intermediate level project in the field of artificial intelligence that one can try. The prerequisites required for these projects are:

1. Programming Knowledge
2. Analytical and logistical thinking.
3. Python Programming.
4. Problem-solving skills.
5. Strong Mathematical Skills.
6. Statistics and modelling solutions.
7. Frameworks.

Primary requirements to do artificial intelligence projects include the analysis of problem statement. Figuring out the edge cases, suitable frameworks, packages. Following agile methodology is strongly recommended if you want to invest yourself in working with artificial intelligence projects.

A proper plan of action is mandatory, things are to be followed before starting the projects.

1. Collecting Information regarding the problem statement.
2. Highlighting the topics which come in handy during the projects.
3. Collecting the dataset.
4. Feature selection.
5. Pre-processing the data.
6. Training the data.
7. Packages and frameworks.
8. Algorithms and coding.
9. Building the model.
10. Implementing the project with new features.

Follow the above steps to build a basic model of your project and then you can implement it with new features and modules. You can then host your model by deploying it into different cloud platforms.