Here we are giving Top machine learning projects ideas with source code.machine learning projects. simple machine learning projects
We are giving the best Machine Learning Projects for Beginners With Source Code for 2022. What projects can I do with machine learning – We get asked this question a lot from beginners getting started with machine learning.
These machine learning projects can be developed in Python, R, or any other tool.
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1. Loan Prediction
Many lending and banking apps now incorporate loan eligibility models. So this is an inspiring angle to start with if you’re interested in applying machine learning to your existing fintech knowledge.
You’re not likely to scale this up for app incorporation, though. But you’ll learn how most enterprise apps decide whether someone is eligible for a loan or not.
To start, you need a dataset containing some financial information. Leveraging the earning and spending trends in this data, you’ll then train your model to learn specific patterns and predict loan eligibility when it receives new information.machine learning projects
2. Sentiment Analysis
Playing around with sentiment analysis is a perfect idea, especially if you have a knack for written words.
If you’re confused, sentiment analysis involves text classification or clustering by a machine, usually into positive and negative perceptions.
As with many natural language projects, feature selection might be a bit challenging here as well. But analyzing sentiments in text often starts with text mining to study the patterns of the texts in question. This lets you figure the main features across your dataset that you can use as training criteria.
You can then use appropriate classification algorithms like the Naive Bayes or the decision tree to train your model. Ultimately, this project exposes you to the basic concepts of text manipulation and how spam detection works.
Python offers a ton of flexible algorithms and logic around sentiment analysis. So if you’re comfortable with Python, which is relatively easy to grasp, you can take a look at how to use the natural language processing toolkit.machine learning projects ideas with source code
3. Code a Logistic Regression Model
Logistic regression is a straightforward classification model perfect for beginners. As you may already know, it finds the probability of occurrence of discrete events.
You can start by working with datasets containing discrete values like “Yes” and “No,” or “Good” and “Bad.” Like other classification algorithms, logistic regression helps your machine encode these into readable values so it can predict appropriately.simple machine learning projects
And if you want to predict more than two possible outcomes, you can delve further into multinomial logistic regression. That said, Python’s scikit-learn might be a pretty handy tool for writing your model.
4. Image Recognition
Technologies like facial recognition and fake image detection might seem like magic. But when you get yourself engrossed in a DIY image recognition project, you’ll soon realize that creating one is easier than you might’ve thought.
Moreover, you have a pretty large handful of image processing machine learning libraries out there at your disposal. TensorFlow, for instance, offers versatile resources for image modeling.
And if TensorFlow is complex to narrow down, Keras, a part of the TensorFlow platform, is also a valuable tool you can leverage. Ultimately, a basic understanding of Artificial Neural Networks (ANN) is helpful for this project.machine learning projects ideas with source code
Your image recognition project, however, may range from fake image detection to image recognition algorithms.
Although it looks tedious at first, it becomes easier as you dive deeper. Plus, it gives you a solid understanding of deep learning concepts.machine learning projects
5. Cancer Classification and Prediction
Cancer classification is an interesting angle to look into, especially if you’re interested in applying your machine learning knowledge in medical fields like bioinformatics.
Your data would typically contain standard metrics for deciding whether a tumor is benign or malignant. You’ll then use this information to create a model that classifies new cancer cases into the appropriate category using the same metrics. Depending on how you intend to approach this, you can use a classification algorithm like the decision tree to inform the machine’s decision.
And if you want to add to the existing knowledge, you can even take your project deeper by delving into cancer prediction. Here, you can use algorithms like Support Vector Machines (SVMs) and Artificial Neural Networks (ANN) to achieve your goal.
6. Stock Price Prediction (Clustering)
The stock market is volatile and prices are based on a plethora of different factors. So, determining a profitable stock can sometimes be an uphill battle for investors.
Because you’re solving a financial-related problem and at the same time learning the basic concepts of machine learning, this project is well worth your time.
Your dataset should contain various stock information and how they’ve changed over time. Because it’s more efficient learning patterns, your model will use this information to predict whether a stock will fall or rise at a point in time. So this is also related to a time series analysis as your model will forecast future outcomes.
And thankfully, many tools are also at your disposal for this project. Facebook’s Prophet, for instance, is an open-source forecasting tool. You can use this with Python. But if you’re more comfortable with R, Prophet also supports R in a massive way.
7. Website Niche Prediction
This isn’t a very popular project for beginners. But you can take it if you like challenges and want to uncover the tools you can use to achieve your aim.
One of the setbacks that you might encounter with this project is where to get datasets. But once you figure out the information you need to solve the problem, you can scrape the data using this BeautifulSoup tutorial.
RELATED: Unique Ways To Get Data For Your Machine Learning Project
To make this work, you need to consider metrics like the headers on a webpage. Additionally, look out for frequently used sentences and keywords, as these are at least pointers to what a webpage is all about. So it means you must select your features carefully for reasonable accuracy.machine learning projects ideas with source code
8. Build a Recommendation System Using Python
You must have come across a recommendation system while browsing the internet or using apps like YouTube and Netflix. Most advertising systems on the internet also use it to filter ads that you see—and sometimes, it feels like the internet knows what you’re thinking.
In some cases, based on what you frequently search on the internet, a recommender might learn about your content preferences. It then uses this to recommend related content that it feels may interest you.
Yours may not be as complex. But you can build something pretty basic to get started. A product recommender, for instance, is an excellent starting spot.
To build a product recommender, for example, you need to gather data about products and people’s perceptions about them. These, of course, might include the number of positive and negative reviews, the product niche, the number of buys, and more.machine learning projects
9. Wine Quality Prediction
Wine quality prediction is one of the few beginner-centric projects. This is a classification problem involving categorizing wine into high and low-quality types.simple machine learning projects
For this, you can use classification algorithms like logistic regression or a decision tree to train your model. You can even use an ANN if you’re more interested in connecting every dot for decision-making.
Like every other machine learning project, this one exposes you to the core concepts of feature selection, correlation, label encoding, and more. Plus, it gives you a leveled playground with your data.
10. Build a Simple Machine Learning Algorithm
While, until this point, we recommended projects that use other algorithms, you can hard code a DIY algorithm from scratch using ML-friendly languages like C, C++, R, or Python.
Although this might sound a bit more challenging than the other tasks on the list, it’s a perfect project idea, especially if you want to know how built-in algorithms work and iterate through your data.
Of course, this doesn’t have to be a complex algorithm. You can look up the mathematical concept behind a simple linear regression, for instance, and use this to create an applicable, reusable, and installable algorithm.
11. Fake News Detection
It’s no news that fake and authentic news flies around the web. But both have unique pointers and attributes that put them in either category.machine learning projects ideas with source code
Because you’re dealing with plain texts, finding a unique descriptive pattern for both news types might give you headway into achieving your goal. You should select your feature carefully to avoid overfitting or underfitting your model.
For this one, you can start by looking at the Natural Language Toolkit documentation, which has many resources that you can use for text processing.
11. Cartoonify Image with Machine Learning
Project Idea: Transform images into its cartoon. Yes, the objective of this machine learning project is to CARTOONIFY the images.
Thus, you will build a python application that will transform an image into its cartoon using machine learning libraries.
12. Iris Flowers Classification Project
Project idea – The iris flowers have different species and you can distinguish them based on the length of petals and sepals.
This is a basic project for machine learning beginners to predict the species of a new iris flower.
13. Emojify – Create your own emoji with Python
Project idea – The objective of this machine learning project is to classify human facial expressions and map them to emojis.
You will build a convolution neural network to recognize facial emotions.
Then you will map those emotions with the corresponding emojis or avatars
14. Loan Prediction using Machine Learning
Project idea – The idea behind this ML project is to build a model that will classify how much loan the user can take.
It is based on the user’s marital status, education, number of dependents, and employments. You can build a linear model for this project.machine learning projects ideas with source code
15. Housing Prices Prediction Project
Project idea – The dataset has house prices of the Boston residual areas.
The expense of the house varies according to various factors like crime rate, number of rooms, etc.
It is a good ML project for beginners to predict prices on the basis of new data.
16. MNIST Digit Classification Machine Learning Project
Project idea – The MNIST digit classification python project enables machines to recognize handwritten digits.simple machine learning projects
This project could be very useful for computer vision.
Here you need to use MNIST datasets to train the model using Convolutional Neural Networks.
17. Stock Price Prediction using Machine Learning
Project idea – There are many datasets available for the stock market prices.
This machine learning beginner’s project aims to predict the future price of the stock market based on the previous year’s data.
18. Titanic Survival Project
Project idea – This will be a fun project to build as you will be predicting whether someone would have survived if they were in the titanic ship or not.
For this beginner’s project, you will use the Titanic dataset that contains real data of the survivors and people who died in the Titanic ship.
19. Wine Quality Test Project
Project idea – In this project, you can build an interface to predict the quality of the red wine.
It will use the chemical information of the wine and based on the machine learning model, it will give you the result of wine quality.machine learning projects
20. Fake News Detection Project
Project idea – Fake news spreads like a wildfire and this is a big issue in this era.
You can learn how to distinguish fake news from a real one. You can use supervised learning to implement a model like this.machine learning projects ideas with source code
21. Zillow Home Value Prediction ML Project
Consider a situation, where you want to buy a house or sell a house, or you are moving to a new city and want to rent a house, but you don’t know where to start. Sometimes, it happens that you know where to start, but you doubt the credibility of the source. Well, some people from Microsoft also felt the need of creating a reliable place that can provide all this information online, and “Zillow” was born in 2006. A few years later, Zillow introduced a feature called “Zestimate”, which has completely changed the market. Zestimate is a tool that provides the worth of the house based on various attributes like public data, sales data, etc. Zestimate has information of more than 97 million homes.
Zestimate is the first step to analyze the worth of a house or to check if the value has been appraised or not after newly upgrading your home, or maybe you just want to refinance it. The algorithm behind Zestimate gets its data 3 times a week, on the basis of comparable sales and publicly available data. As per Zillow, Zestimates are within the range of 10% of the selling price of homes. By providing the approximate value ranges of the properties, Zillow balances the inaccuracy in the pricing, We can assume that the smaller the range, the more accurate will be the estimated price of the property, this is due to the fact, that Zillow will be having more data for that property. Using Zestimate, users can guess their home’s worth by checking the boundary values.
Project Idea: In this Machine Learning project for final year students, you will use the Zillows Economics dataset to build a house price prediction model with XGBoost based on factors like average income, crime rate, number of hospitals, number of schools, etc. Having completed this top ML project one should be able to answer questions like top States with highest rent Values, in which state should you buy/rent a house, Zestimate per square feet, the median rental price for all homes, etc.
22. BigMart Sales Prediction ML Project – Learn about Unsupervised Machine Learning Algorithms
As a beginner, you should work on different machine learning projects ideas to diversify your skillset. Thus, we have added a project that will introduce unsupervised machine learning algorithms to you by using the sales dataset of a grocery supermarket store.
Project Idea: BigMart sales dataset consists of 2013 sales data for 1559 products across 10 different outlets in different cities. The goal of the BigMart sales prediction ML project is to build a regression model to predict the sales of each of 1559 products for the following year in each of the 10 different BigMart outlets. The BigMart sales dataset also consists of certain attributes for each product and store. This model helps BigMart understand the properties of products and stores that play an important role in increasing their overall sales.
23. Music Recommendation System ML Project
This is one of the most popular machine learning projects and can be used across different domains. You might be very familiar with a recommendation system if you’ve used any E-commerce site or Movie/Music website. In most E-commerce sites like Amazon, at the time of checkout, the system will recommend products that can be added to your cart. Similarly on Netflix or Spotify, based on the movies you’ve liked, it will show similar movies or songs that you may like. How does the system do this? This is a classic example where Machine Learning can be applied.
Project Idea: In this project, we use the dataset from Asia’s leading music streaming service to build a better music recommendation system. We will try to determine which new song or which new artist a listener might like based on their previous choices. The primary task is to predict the chances of a user listening to a song repetitively within a time frame. In the dataset, the prediction is marked as 1 if the user has listened to the same song within a month. The dataset consists of which song has been heard by which user and at what time.
24. Iris Flowers Classification ML Project
This is one of the most simple machine learning projects with Iris Flowers being the simplest machine learning datasets in classification literature. This machine learning problem is often referred to as the “Hello World” of machine learning. The dataset has numeric attributes and ML beginners need to figure out how to load and handle data. The iris dataset is small which easily fits into the memory and does not require any special transformations or scaling, to begin with.simple machine learning projects
Iris Dataset can be downloaded from UCI ML Repository – Download Iris Flowers Dataset The goal of this machine learning project is to classify the flowers into among the three species – virginica, setosa, or versicolor based on length and width of petals and sepals.machine learning projects ideas with source code
25.Stock Prices Predictor using TimeSeries
This is another interesting machine learning project idea for data scientists/machine learning engineers working or planning to work with the finance domain. A stock prices predictor is a system that learns about the performance of a company and predicts future stock prices. The challenges associated with working with stock price data is that it is very granular, and moreover there are different types of data like volatility indices, prices, global macroeconomic indicators, fundamental indicators, and more. One good thing about working with stock market data is that the financial markets have shorter feedback cycles making it easier for data experts to validate their predictions on new data. To begin working with stock market data, you can pick up a simple machine learning problem like predicting 6-month price movements based on fundamental indicators from an organizations’ quarterly report. You can download Stock Market datasets from Quandl.com or Quantopian.com. There are different time series forecasting methods to forecast stock price, demand, etc.
Project Idea: Stock Market Prediction in Python using Time Series Forecasting
A time series is an analysis of event occurrences over a period of time. A time series is analyzed to identify patterns so that future occurrences can be predicted based on trends observed over a period of time. A time series is a good way to get an idea of seasonal variation, repetitive patterns and even to identify unexpected events to further understand what could have caused them. To perform time-series forecasts, there are various models that can be used. The selection of the model itself is dependent on various factors which include: the availability of the past data, the context of the forecast, the time period for which the forecast has to be made, and the time available to create the model and make the forecast. Some of the models which can be used for time series forecasting are moving-average, exponential smoothing, and ARIMA (autoregressive integrated moving average) model. The moving average model is a very straightforward modeling technique that predicts the next occurrence to be the mean of all the past occurrences. Although it seems very simple, it has been found to be quite accurate in many places. In the case of exponential smoothing, the mean is calculated by giving less weightage to occurrences that are further away from the present. This means that more recent occurrences have more value towards the calculation of the mean than older events. The ARIMA model is a slightly more complex model. It is a form of regression analysis that monitors the strength of one dependent variable based on other changing variables.Check out the source code machine learning project to learn how to determine which forecasting method to be used when and how to apply it with time series forecasting example.machine learning projects
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26. Predicting Wine Quality using Wine Quality Dataset
It’s a known fact that the older the wine, the better the taste. However, there are several factors other than age that go into wine quality certification which include physiochemical tests like alcohol quantity, fixed acidity, volatile acidity, determination of density, pH, and more.
Project Idea: The main goal of this machine learning project is to build a machine learning model to predict the quality of wines by exploring their various chemical properties. The wine quality dataset consists of 4898 observations with 11 independent and 1 dependent variable.
27. MNIST Handwritten Digit Classification
Deep learning and neural networks play a vital role in image recognition, automatic text generation, and even self-driving cars.
Project Idea: To begin working in these areas, you need to begin with a simple and manageable dataset like the MNIST dataset. It is difficult to work with image data over flat relational data and as a beginner, we suggest you can pick up and solve the MNIST Handwritten Digit Classification Challenge. The MNIST dataset is too small to fit into your PC memory and is beginner-friendly. However, handwritten digit recognition will challenge you.
28. Build a Movie Recommender System Movielens Dataset
From Netflix to Hulu, the need to build an efficient movie recommender system has gained importance over time with increasing demand from modern consumers for customized content. One of the most popular datasets available on the web for beginners to learn building recommender systems is the Movielens Dataset which contains approximately 1,000,209 movie ratings of 3,900 movies made by 6,040 Movielens users. You can get started working with this dataset by building a world-cloud visualization of movie titles to build a movie recommender system
29. Boston House Pricing Prediction Project
Boston House Prices Dataset consists of prices of houses across different places in Boston. The dataset also consists of information on areas of non-retail business (INDUS), crime rate (CRIM), age of people who own a house (AGE), and several other attributes (the dataset has a total of 14 attributes). machine learning projects ideas with source code
30. Social Media Sentiment Analysis Using Twitter Dataset
Social media platforms like Twitter, Facebook, YouTube, Reddit generate huge amounts of big data that can be mined in various ways to understand trends, public sentiments, and opinions. Social media data today has become relevant for branding, marketing, and business as a whole. A sentiment analyzer learns about various sentiments behind a “content piece” (could be IM, email, tweet, or any other social media post) through machine learning and predicts the same using AI.Twitter data is considered a definitive entry point for beginners to practice sentiment analysis machine learning problems.
Project Idea: Using the Twitter dataset, one can get a captivating blend of tweet contents and other related metadata such as hashtags, retweets, location, users, and more which pave way for insightful analysis. The Twitter dataset consists of 31,962 tweets and is 3MB in size. Using Twitter data you can find out what the world is saying about a topic whether it is movies, sentiments about US elections, or any other trending topic like predicting who would win the FIFA world cup 2018. Working with the Twitter dataset will help you understand the challenges associated with social media data mining and also learn about classifiers in depth. The foremost problem that you can start working on as a beginner is to build a model to classify tweets as positive or negative.machine learning projects
31. Music Genre Classification Machine Learning Project
Project Idea: The idea behind this python machine learning project is to develop a machine learning project and automatically classify different musical genres from audio.
You need to classify these audio files using their low-level features of frequency and time domain.
32. Bitcoin Price Predictor Project
Project idea – The bitcoin price predictor is a useful project. Blockchain technology is increasing and there are many digital currencies rising.
This project will help you predict the price of the bitcoin using previous data.
33. Uber Data Analysis Project
Project idea – The project can be used to perform data visualization on the uber data. The dataset contains 4.5 millions of uber pickups in the new york city.
This much data needs to be represented beautifully in order to analyze the rides so that further improvements in the business can be made.
34. Personality Prediction Project
Project idea – The Myers Briggs Type Indicator is a personality type system that divides a person into 16 distinct personalities based on introversion, intuition, thinking and perceiving capabilities.
You can identify the personality of a person from the type of posts they put on social media.
35. Handwritten Character Recognition
Project Idea: In this machine learning project, you will detect & recognize handwritten characters, i.e, English alphabets from A-Z.
You are going to achieve this by modeling a neural network.
36. Xbox Game Prediction Project
Project idea – The data generated by people while searching can be used to predict the interest of the users.
The BestBuy consumer electronics company has provided the data of millions of searches from users and you will predict the Xbox game that a user will be most interested to buy.
This will be used to recommend games to the visitors.
37. Credit Card Fraud Detection Project
Project idea – Companies that involve a lot of transactions with the use of cards need to find anomalies in the system.
The project aims to build a fraud detection model on credit cards.
You need to use the transaction and their labels as fraud or non-fraud to detect if new transactions made by the customer are fraud or not.machine learning projects ideas with source code
38. Sign Language Recognition with Machine Learning
Project Idea: A lot of research has been done to help people who are deaf and dumb.
In this sign language recognition project, you create a sign detector that detects sign language.
This can be very helpful for the deaf and dumb people in communicating with others
39. Barbie with Brains Project
Project idea – Kid toys like barbie have a predefined set of words that they can speak repeatedly.
You can use machine learning methods to give the barbie some brain.
It will be more engaging when a toy can understand and speak with different sentences.
This is an excellent project that will improve the learning process of kids.
40. Customer Segmentation using Machine Learning
Project idea – Customer segmentation is a technique in which we divide the customers based on their purchase history, gender, age, interest, etc.
It is useful to get this information so that the store can get help in personalized marketing and provide customers with relevant deals.
With the help of this project, companies can run user-specific campaigns and provide user-specific offers rather than broadcasting same offer to all the users.machine learning projects ideas with source code