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.

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.

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

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.

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.

The MNIST digit classification python project enables machines to recognize handwritten digits.

This project could be very useful for computer vision.

Here you need to use MNIST datasets to train the model using Convolutional Neural Networks.

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.

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.

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.

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.

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.

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.

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.

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.

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 modelling a neural network.

The data generated by people while searching can be used to predict the interest of the users.

The Best Buy 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.

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.

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

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.

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 personalize 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.

You can categorize their emotions as positive, negative or neutral.

It is a great project to understand how to perform sentiment analysis and it is widely being used nowadays.

This is one of the most popular machine learning projects. The reason behind this is every company is trying to understand the sentiment of their customers if customers are happy, they will stay.

This project could show a path to reduce customer churn.

The Enron company collapsed in 2000 but the data was made available for investigation.

The database has 500,000 emails of real employees who worked in the company so the data is very useful to perform data analytics and many data scientist use this dataset.

This is one of the best machine learning projects. The speech emotion recognition system uses audio data.

It takes a part of speech as input and then determines in what emotions the speaker is speaking.

You can identify different emotions like happy, sad, surprised, angry, etc. This project could be helpful for identifying customer emotions during the call with the call centre.

There are many ships, boats on the oceans and it is impossible to manually keep track of what everyone is doing.

It will be an amazing project that can identify illegal poaching of animals and catch fishing activities through satellite and Geolocation data.

The Global Fishing Watch is offering real-time data for free, that can be used to build the system.

Collaborative filtering is a great technique to filter out the items that a user might like based on the reaction of similar users.

A grocery recommendation system would be a great project to make customers realize what they would like in their baskets.

It is good for those who are planning to start the Grocery Store.

Recommendation systems are everywhere, be it an online purchasing app, movie streaming app or music streaming.

They all recommend products based on their targeted customers. A movie recommendation system is an excellent project to enhance your portfolio.

Project idea: The objective of this machine learning project is to detect and recognize the license number plate of a vehicle and read the license numbers printed on the plate.

This could be a good application for security scans, traffic monitoring, etc.

Predict location as well as class to which each object in the image belongs.

Image segmentation results in granular level information about the shape of an image and thus an extension of the concept of Object Detection

The Python opencv library is mostly preferred for computer vision tasks. You can detect all the edges of different objects of the image.

Computer vision can be used to process images and perform various transformations on the image.

The idea is to build an app that will take an image as input from the user and convert it into a pencil sketching.

Contours are outlines or the boundaries of the shape. You can build a project to detect certain types of shapes.

For example: with a round shape, you can detect all the coins present in the image.

The project is good to understand how to detect objects with different kinds of shapes.

A collage mosaic is an image that is made up of thousands of small images.

To get a clear bigger picture composed of many small images it is required to position images properly according to the colors in the image.

You can build an app that will generate a big collage mosaic comprising hundreds of images inside.

Have you ever use the panorama mode in your smartphones?

Once you dive into computer vision, then you can build your own panorama app and it is very interesting to understand how panorama works.

Object tracking is the process of identifying where a particular object is present in the image.

Camshift algorithm is an effective way to track an object when the object size varies and rotates while moving.

QR code and barcodes are used everywhere and they store some information in them.

You can detect the QR code and Barcode from the image to process it further and decode the encrypted data.

In the harry potter movie, Harry uses an invisible cloak that lets the light pass through them. You can see what’s behind the cloak.

That is what you are going to build in this project.

Many businesses require watermarking on all the images. It is a repetitive task that needs to be automated.

You can build a project to automate the watermarking task on all images provided to the application.

Face detection is a technique to find the location of the human faces in an image.

Computers use various types of algorithms to detect if the shape in the image resembles a face or not.

You can build an app to automatically detect faces and capture the image in our system.

Blurring the face area of people from videos is done in all news channels and to hide the identity of a person.

With computer vision, You can automatically detect the face region of the person and use it to blur the image.

The project will be useful in blurring the faces of the people in the video.

Image segmentation is the process of dividing an image into multiple segments.

It is very useful in finding meanings from the image. They are used in object detection of self-driving cars.

In this project, you can build an application to upload the image on the app.

Then by performing different transformations on the image we can make the image look like a cartoon.

A camera can be used to monitor and count the number of people present in the room, building, street, etc.

First, you need to detect people and then we count their occurrence. It is useful to control the crowd.

Document images taken from the camera can contain background, and their perspective is not aligned properly.

So you can build a document scanner app that will fix this by detecting the edges of the document and then transform the perspective.

This is an interesting project in which you can draw anything by moving your hands in the air.

The project will use a camera to detect the fingertip and then we can draw the shape on the canvas.

Build a simple app that is responsible for detecting a particular color from the image.

There are millions of different types of colors and you cannot name each of them.

So you can use thousands of named colors to identify which color resembles close to the pixel from the image.

In a face recognition app, you not only detect if this is a face or not, you further recognize whose face is it.

This is very useful in labeling people’s names and also authenticating using face.

This project requires you to first feed data of the people you want to recognize and then you train the model that can recognize people.

In this project, you are going to determine the gesture of the hand in real-time using a webcam.

First, the background is separated from the hand region and then the fingers are segmented to predict hand gestures.

With different hand gestures, you can perform different actions.

You know it’s hard to take a beautiful picture of your dog as they are restless and always moving.

To solve this problem, you can make a system that will capture the image of the dog when the dogs are smiling and looking directly at the camera.

You can use the computer vision techniques to classify vehicles on the road, HMV(heavy motor vehicle) or LMV( light motor vehicle) and also count the number of vehicles that travel through a road.

The data can be stored to analyze the different vehicles that travel from a road.

To perform deep learning and machine learning, you need lots of data that is hard to find.

Data augmentation techniques are used a lot to increase the size of the dataset by performing rotations, transformations, zooming, flipping, etc.

In this project, you can build an interface to select the augmentation method and then generate more data.

Everyone loves a smiling picture, so how about making a camera app project which will capture images every time you smile.

So for this, you need to build a model to identify whether a person is smiling or not.

The idea behind this project is to make a virtual drum that you can play by using a stick in the air.

For this, the stick should be colored in the end that you will use to locate the position of stick and when it reaches a certain position a drum sound would be played.

A challenge is to also measure the sound intensity based on the speed of the stick movement.

The computer vision techniques can be used to find images that are similar to the selected image.

You need a database containing lots of images and then you can select an image to find similar images from the database.

A king of yellow journalism, fake news is false information and hoaxes spread through social media and other online media to achieve a political agenda. In this data science project idea, we will use Python to build a model that can accurately detect whether a piece of news is real or fake. We’ll build a TfidfVectorizer and use a PassiveAggressiveClassifier to classify news into “Real” and “Fake”. We’ll be using a dataset of shape 7796×4 and execute everything in Jupyter Lab.

The lines drawn on the roads guide human drivers where the lanes are. It also refers to the direction to steer the vehicle. This application is cardinal for developing driverless cars.

You can build an application having the ability to identify track lines from input images or continuous video frames.

Sentiment analysis is the act of analyzing words to determine sentiments and opinions that may be positive or negative in polarity. This is a type of classification where the classes may be binary (positive and negative) or multiple (happy, angry, sad, disgusted,..). We’ll implement this data science project in the language R and use the dataset by the ‘janeaustenR’ package. We will use general-purpose lexicons like AFINN, bing, and loughran, perform an inner join, and in the end, we’ll build a word cloud to display the result.

We have started using data science to improve healthcare and services – if we can predict a disease early, it has many advantages on the prognosis. So in this data science project idea, we will learn to detect Parkinson’s Disease with Python. This is a neurodegenerative, progressive disorder of the central nervous system that affects movement and causes tremors and stiffness. This affects dopamine-producing neurons in the brain and every year, it affects more than 1 million individuals in India.

How many times has it occurred to you that even after seeing, you don’t remember the name of the color? There can be 16 million colors based on the different RGB color values but we only remember a few. So in this project, we are going to build an interactive app that will detect the selected color from any image. To implement this we will need a labeled data of all the known colors then we will calculate which color resembles the most with the selected color value.

There are many famous deep learning projects on MRI scan dataset. One of them is Brain Tumor detection. You can use transfer learning on these MRI scans to get the required features for classification. Or you can train your own convolution neural network from scratch to detect brain tumors.

Disease detection in plants plays a very important role in the field of agriculture. This Data Science project aims to provide an image-based automatic inspection interface. It involves the use of self designed image processing and deep learning techniques. It will categorize plant leaves as healthy or infected.

This data science project uses librosa to perform Speech Emotion Recognition. SER is the process of trying to recognize human emotion and affective states from speech. Since we use tone and pitch to express emotion through voice, SER is possible; but it is tough because emotions are subjective and annotating audio is challenging. We’ll use the mfcc, chroma, and mel features and use the RAVDESS dataset to recognize emotion on. We’ll build an MLP Classifier for the model.

This is an interesting data science project with Python. Using just one image, you’ll learn to predict the gender and age range of an individual. In this, we introduce you to Computer Vision and its principles. We’ll build a Convolutional Neural Network and use models trained by Tal Hassner and Gil Levi for the Adience dataset. We’ll use some .pb, .pbtxt, .prototxt, and .caffemodel files along the way.

Diabetic Retinopathy is a leading cause of blindness. You can develop an automatic method of diabetic retinopathy screening. You can train a neural network on retina images of affected and normal people. This project will classify whether the patient has retinopathy or not.

This is a data visualization project with ggplot2 where we’ll use R and its libraries and analyze various parameters like trips by the hours in a day and trips during months in a year. We’ll use the Uber Pickups in New York City dataset and create visualizations for different time-frames of the year. This tells us how time affects customer trips.

Drowsy driving is extremely dangerous and around thousands of accidents happen each year due to drivers falling asleep while driving. In this Python project, we will build a system that can detect sleepy drivers and also alert them by beeping alarm.

This project is implemented using Keras and OpenCV. We will use OpenCV for face and eye detection and with Keras, we will classify the state of the eye (Open or Close) using Deep neural network techniques.

Chatbots are an essential part of the business. Many businesses has to offer services to their customers and it needs a lot of manpower, time and effort to handle customers. The chatbots can automate most of the customer interaction by answering some of the frequent questions that are asked by the customers. There are mainly two types of chatbots: Domain-specific and Open-domain chatbots. The domain-specific chatbot is often used to solve a particular problem. So you need to customize it smartly to work effectively in your domain. The Open-domain chatbots can be asked any type of question so it requires huge amounts of data to train.

The MNIST dataset of handwritten digits is widespread among the data scientists and machine learning enthusiasts. It is an amazing project to get started with the data science and understand the processes involved in a project. The project is implemented using the Convolutional Neural Networks and then for real-time prediction we also build a nice graphical user interface to draw digits on a canvas and then the model will predict the digit.

This is an interesting data science project. Describing what’s in an image is an easy task for humans but for computers, an image is just a bunch of numbers that represent the color value of each pixel. So this is a difficult task for computers to understand what is in the image and then generating the description in Natural language like English is another difficult task. This project uses deep learning techniques where we implement a Convolutional neural network (CNN) with Recurrent Neural Network( LSTM) to build the image caption generator.

By now, you’ve begun to understand the methods and concepts. Let’s move on to some advanced data science projects. In this project, we’ll use R with algorithms like Decision Trees, Logistic Regression, Artificial Neural Networks, and Gradient Boosting Classifier. We’ll use the Card Transactions dataset to classify credit card transactions into fraudulent and genuine. We’ll fit the different models and plot performance curves for them.

In this data science project, we’ll use R to perform a movie recommendation through machine learning. A recommendation system sends out suggestions to users through a filtering process based on other users’ preferences and browsing history. If A and B like Home Alone and B likes Mean Girls, it can be suggested to A – they might like it too. This keeps customers engaged with the platform.

This is one of the most popular projects in Data Science. Before running any campaign companies create different groups of customers.

Customer Segmentation is a popular application of unsupervised learning. Using clustering, companies identify segments of customers to target the potential user base. They divide customers into groups according to common characteristics like gender, age, interests, and spending habits so they can market to each group effectively. We’ll use K-means clustering and also visualize the gender and age distributions. Then, we’ll analyze their annual incomes and spending scores.

Coming back to the medical contributions of data science, let’s learn to detect breast cancer with Python. We’ll use the IDC_regular dataset to detect the presence of Invasive Ductal Carcinoma, the most common form of breast cancer. It develops in a milk duct invading the fibrous or fatty breast tissue outside the duct. In this data science project idea, we’ll use Deep Learning and the Keras library for classification.

Traffic signs and rules are very important that every driver must follow to avoid any accident. To follow the rule one must first understand how the traffic sign looks like. A human has to learn all the traffic signs before they are given the license to drive any vehicle. But now autonomous vehicles are rising and there will be no human drivers in the upcoming future. In the Traffic signs recognition project, you will learn how a program can identify the type of traffic sign by taking an image as input. The German Traffic signs recognition benchmark dataset (GTSRB) is used to build a Deep Neural Network to recognize the class a traffic sign belongs to. We also build a simple GUI to interact with the application.