Machine Learning, an offshoot of Artificial Intelligence is one of the hottest technologies right now. It is the study of computer algorithms which enhances along with experience and with the use of data. Machine learning algorithms predict and perform actions without being ordered to do so based on training data or the sample data. In simple terms as the name suggests when the machine develops a mind of itself (thus machine learning), well not literally but as the data gets fed and trained the machine (algorithm) becomes intelligent enough to predict any future action. In a world like today machine learning technology is pretty much everywhere but we as a layman just fail to understand and identify it. From Spotify to Netflix, Siri, Amazon and so on machine learning technology is everywhere. Among the tech enthusiasts it is a big hit and every minute techies are trying to build a new machine learning model for use in various fields. If you are also a tech enthusiast and want to try your hands on machine learning here are some interesting projects to start with.
1. Recommendation System
This can be considered as one of the most popular uses of machine Learning Technology. This is being applied to all the online video streaming platforms and online music streaming platforms. Apart from these, shopping websites, book reading platforms and social media also make use of this machine learning technology. It was in 2006 when Netflix was on a lookout for a software/program which could better predict the user preferences, they did this by holding a competition for which the winner would be rewarded with $1 Million. It was a team made up of Big Chaos, AT&T Labs-Research and Pragmatic theory who won by building an ensemble model. Ever since then Machine learning in recommendations has been hot. For a beginner, to develop a recommendation system for a movie website, music platform or travel website would be great because the internet is filled with data sets for these.
2. Real Estate Price Prediction
Real estate is one of the major sectors of any economy. The ever changing housing and real estate market is not that easy to crack. But with Machine Learning this has been possible, many ML models have been developed to predict housing prices and real estate prices. Though the accuracy rate has been one of the major challenges it can be a fun project to start if you are a Machine Learning enthusiast. Real data sets can be found via various public domains. A well developed model can turn into something groundbreaking in the real estate market, as buying a house or a property is a huge investment cum risk for any individual or an organization. This project can even be taken up a notch by adding property recommendation features for clients, a predictive analytics chart of the properties which are doing good and properties which are not.
3. Crypto Predictor
Cryptocurrency is currently the thing among the millennials and tech lovers. Ever since the emergence of Bitcoin in 2008, cryptocurrency has found its importance in the business world. Cryptocurrency owners and investors are always looking into the charts to see where the prices are going. So developing a cryptocurrency predictor can be a very interesting project for someone who is starting out in Machine Learning. To start with this project you will need the real time crypto currency data. Data for cryptocurrency are generally divided under five categories namely Close price ( the market close price for currency on that particular day), High price (highest price for currency on that day), Low price (the lowest price for the currency on that day), Open price (Market open price for the currency on that day) and Volume (volume of currency which is being in trade for that day). With the availability of so much data you can easily start a machine learning project to predict cryptocurrency prices.
4. Sports Prediction
It is really a great machine learning project for beginners mainly because of the availability of data. A simple beginner project in sports prediction can be scouting. Yes, machine learning can be used in scouting new players whether it is scouting a rookie or a pro player. For rookie players you can take data from any college and university level sports competition and predict which player has a higher chance of having a good career. Similarly, if we talk about professional players, the data is available all over the internet and that data can be trained and tested for machine learning prediction and building a new model.
5. Emoji Creation
Everyone loves using emojis in their texts, it fills that emotional gap between the people texting. Originally started with emoticons which were made using characters (mainly punctuation marks, numbers and letters) it has grown into a plethora of emojis. When the emojis first popped up in the 2000s, there were only a number of them which were mostly facial expressions but today there are all kinds of emojis. These range from different facial expressions to food items, daily use items, nature, buildings, landscapes etc. So for a Machine Learning beginner, creating emojis using the study of human facial expression can be a very fun project.
6. Stock Price Prediction
Stock market is known as one of the most unpredictable and a hard nut to crack but with machine learning even this is possible. For a beginner this can be a great project since there is a whole bunch of data available on the stock market. Many businesses and organizations are closely watching any development on softwares for stock price prediction. This means the opportunity to make it big with a software that monitors and analyses the performance of their business and predicts the future stock prices is vast. To start this project off, one should be familiar with various predictive techniques such as Predictive analysis, Regression analysis, Action Analysis and statistical modelling.
7. Image Recognition
Image recognition is being used by many applications and devices today, not only this but even many organizations make use of this technology. It is a very fascinating technology where the machine identifies an image (by classifying it), analyses it and takes decisions accordingly. Developing a new image recognition system can be an exciting project for beginners in Machine Learning. You build an image classification model which identifies to which category the input image belongs to and how will it react. Get the data from any public domain and train it to build your model.
8. Anomaly Detection
Anomaly detection is a very important step in data mining where rare and uncommon events are identified so as to look out for any suspicious behaviours. These are mainly used in Credit Card Fraud Detection Systems by detecting unusual behaviour, rare events and occurrences i.e unusual transactions etc. Working on something of this sort i.e. fraud detector to identify fraudulent or intrusive behaviour can be a great project for machine learning beginners.
9. Social Media Mining
Social media is so prevalent on this day and age. Whether it is microblogging sites, photo/video sharing platforms or platforms simply made for social interactions, people not only use them for personal purposes but things run a lot deeper. Social media is extremely influential from raising funds to turning election poll results. This sea of data can be collected, analysed and processed to predict whether a certain social media post will get enough reach or not. Beginners in machine learning can take up this project and build a model to mine social media data.
10. Sentiment Analysis
It is another hugely popular machine learning application used by many businesses to understand the response of their customers. Many businesses are on a look out for sentiment analysis software that can guarantee them good results. This process helps businesses identify their flaws eventually leading to improvement. So a project to build sucha software should entice any machine learning enthusiast. Sentiment Analysis is done by processing natural language, analyzing texts and by using biometrics, computational systems to systematically identify, extract, evaluate and study emotional state and subjective information i.e identifying positive or negative sentiment in a text. In this project you can classify user sentiments as positive, negative or neutral.
11. Medical Diagnosis
Since machine learning works on data and predictive analysis one of it’s recently evolving applications has to be medical diagnosis. Doctors study so much and fill their minds with all the data present in the textbooks, then they use that data, a patient’s physical state, psychological state, genetic factors and environmental factors to diagnose a disease. Now, building a model which has been fed with all the clinical data in a classified manner can be resulted into a diagnosis providing software and can be a really interesting project to start off as a beginner in machine learning. Though this might sound easy, to really pull it off there are going to be a lot of challenges to be tackled since one failed diagnostic can lead to a disastrous result.
12. MNIST Digit Classification
This is another really interesting project for beginners as the data is easily available for training and testing your model. Especially, if you are building an image processing system it is the way to begin. MNIST (Modified National Institute of Standards and Technology) database is a huge database which includes handwritten digits, 0 through 9. These handwritten digits can act as a baseline for an image processing system and you can train your model to recognise handwritten digits.
13. Human Activity Recognition Via Smartphone
This machine learning project will entice any beginner. Human Activity Recognition simply known as HAR is basically to predict what a person is doing i.e. activities such as standing, sitting, running, walking up the stairs, down the stairs etc. This is done by tracing their movements using sensors located in smartphones which record accelerometer data on three dimensions. To build a model for HAR sensor dataset can be collected and trained, a dataset called Activity Recognition Using Smartphones was made available to public domain in 2012 by David Anguita and a few others from University of Genova, Italy.
14. Fake News Detection
Fake news is one of the most tricky modern day problems. It spreads like wildfire causing panic and distress among people. Detecting fake news among the real ones is a challenge and to build a model to do that would be a really exciting project for machine learning beginners. Most of our lives are dominated by social media these days. On top of that most of the people use social media as a source of news this leads to belief in a lot of fake news and rumours. With machine learning technology fake news can be easily detected and classified accordingly.
15. Exploratory Analysis
Data is everything in business today. All things work around the data collected and analyzed which means big of the biggest decision taken by an organisation is based on it. Data scientists analyzing these data use Exploratory Data Analysis, a very critical technique to find out hidden patterns and trends. In simple words a way to visualize, summarize and interpret the hidden patterns in rows and columns. For beginners in Machine Learning just getting familiar with this technique and getting more hands on with it can be great.