Latest Projects Based on Machine Learning

The ever-increasing suicide rate is alarming. Experts are trying to understand the various reasons for suicide. From college going students to CEO of MNCs, there are a lot of cases. By doing this project you will try to save some lives by detecting suicidal tendencies.

Stock market prediction is the way of predicting future prices and values of the companies. This application will give investors more confidence to invest in a particular company. By using this application, the investors can keep track of the profits and losses in the stocks. The application is developed through a machine learning model and is used to predict stock prices.

Wine predictor is used for predicting the quality and taste of wine on a scale of 0-10. It requires a set of inputs, which is based on many other parameters such as acidity, concentration, etc. The project involves the concept of machine learning, which thoroughly studies the pattern and data and predicts the results.

Project on Iris Flower Classification using machine learning is simple and is one of the most basic projects if someone wants to learn about machine learning. This project is basically used to differentiate between three species of the Iris flower, which are setosa, versicolor, and virginica.

Bigmart is a vast supermarket chain which is located nearly at every megacity. The sales of Bigmart are very crucial, and data scientists study those patterns per product and per store to decide about the new centers. Using machine learning to predict Bigmart sales enables the data scientist to do so, as it studies the various patterns per store and per product to give accurate results.

Sentiment analysis is basically the computational determination of whether the piece of content is positive or negative. This analysis is also known as Opinion Mining; it earns a great use in today’s world. This application can be helpful in deciding the sentiments in the tweets of the people. As Twitter is a huge platform for opinions, and it affects a large number of people, the application can be helpful in reducing the hatred on the Internet.

The objective of the project is to build an application that could predict the sales using the Walmart dataset. This application will help in providing us with the data on future sales, and hence we can improve the sales of the company. Walmart is one of the biggest retail services in the world. With 45 stores across the world, the data associated with it is huge in number.

There are various potential projects in healthcare that are based on machine learning algorithms. In this project, we will discuss the heart-related disease diagnosis application, which is built with the concept of data analysis and machine learning. There is a great demand for this project in the real world, also, as doctors throughout the world want to detect the disease accurately.

The mysterious bankruptcy of the Enron Corporation has led to the development of this project. This project is built to investigate this case on the huge data set of this fraud business, which took place in December 2001. The data set mainly comprises the millions of e-mails sent to and from the executives of the company during the year 2000-2002. The nature of emails was reported to be suspicious, and hence it was not possible for anyone to decide nature.

Human Activity Recognition is the project meant for tracking the activities of humans in their daily life. This project is based on the pattern study and data filtration, which is obtained through machine learning. Machine learning will help to study the huge data variations of human activities. The project is highly useful in medical assistance, elder care, rehabilitation assistance, diabetes, and cognitive disorders domain.

MNSIT simply stands for Modified National Institute of Standards and Technology dataset. The application is based on machine learning of the huge data set available, and it helps to recognize a particular digit into a class of 10. The application is widely used in visual training and digit recognition. The application also uses many algorithms and classifiers.

Our world is heavily driven by technology and one of the newest facets of technology which is getting a lot of attention is machine learning. This field of study hopes to transform simple machines into smart machines that can think and analyze problems, much like how we do! In this post, we will be looking at one of the large scale applications of machine learning which is sports analytics. So here’s a look at a Moneyball inspired Sports Analyser project that works on the principles of Machine Learning.

As technology surges ahead, some of the most important developments have been ones that help us save time, because as we know, time is money in the twenty-first century. Handwriting analysis has been trying to make a ripple within the industry for a while now, as they would make it a lot easier for people to upload documents onto the web. Such character recognition works on the principles of artificial intelligence, computer vision, machine learning, and pattern recognition. Computers that can analyse handwriting and recognise or detect characters will be able to convert the paper documents into machine-readable form. Here’s a look at a simple Handwriting reader project using machine learning.

There are few people alive right now who haven’t heard of Netflix and Spotify. Both these global brands have grown exponentially in the past few years, and have now become one of the most widely recognised brands of all time. One of the most significant things both of them have in common, other than being a streaming service, is that they both have amazing recommendation software. Netflix’s recommendation has built a name for itself, giving customers exactly what they want, time and time again. Seeing the popularity that such a system has, other tech giants such as Amazon and Google are also working on their own recommendations application. In this Machine Learning project, we will be taking a look at how to build such an app on our own.

Whenever a crisis occurs, one of the most important tasks that disaster forces have is rescuing trapped humans. This holds true especially in case of natural disasters such as earthquakes and volcano eruptions, and also when it comes to large outbreaks of fire. Ensuring that victims are rescued is a number one priority in such cases, as being exposed to toxic fumes for too long can lead to death. So how do we develop a full-proof method to find victims in such cases? Surely, there are a lot of restrictions for humans when it comes to such adverse situations. Thanks to advancements in science and technology, we can now use autonomous vehicles and robots to go where humans can't and to rescue victims in situations that were previously impossible to us. In this article, we will be taking a look at one such project, where we will attempt to build a rescue robot using the principle of computer vision.

It’s not always easy to pick the right movie to watch. Sometimes you're in the state of mind to see individuals begin to look all starry eyed at, or you need a motion picture to remind your connection with music, or you need to just watch characters to whom you relate or any emotion-based movie. Settling on this decision can't generally be understood by attempting to pick something dependent on genre. This is why we are going to create,  a “Movie recommendation system based on emotion”, which enables us to choose movies based on how you want their viewing experience to make them feel.

Sign languages (also known as signed languages) are languages that utilize the visual-manual methodology to pass on importance. Language is communicated through the manual sign stream in the mix with non-manual components.

Communication via gestures is a visual language that is utilized by hard of hearing and almost deaf individuals as their first language, it is additionally utilized by hearing people, for example, the individuals who experience difficulty with communicated in language because of an incapacity or condition individuals. To the extent a hard of hearing individual is concerned, approaching sign language communication is significant for their social, enthusiastic and semantic development. This framework is to help hearing-hindered individuals in India cooperate with others as it makes an interpretation of English text to Sign language.

In this machine learning project, we need to build up a mathematical model for predicting the success class, for example, flop, hit, the super hit of the films. For doing this we need to build up a system in which the historical data of each component such as actor, actress, director, music that influences the success or failure of a movie is given. Then depend on different edges determined based on the basis of descriptive statistics of a dataset of each component will give flop, hit, super hit label. So, in this article, we are going to explore how to implement Movie success prediction using data mining. I hope you’re excited to see and learn the process of making the project. So, without any further delay, let get started!

To start with, you have to get acquainted with "What is phishing website?”,  So various clients buy items on the web and make installments through different sites. Numerous sites request that the client give touchy information, for example, username, password or credit card or bank details, etc. often for malicious reasons. This sort of site is known as a phishing website. To distinguish and anticipate a phishing site, we proposed a savvy, adaptable and successful framework that depends on ML. We implemented some algorithms and techniques to extract the phishing data for setting the criteria to classify their legitimacy. The phishing site can be recognized dependent on some significant qualities like URL and Domain Identity, and security and encryption criteria in the last phishing location rate. With the assistance of this framework, the client can likewise buy items online decisively. The administrator can include phishing site URL or phony site URL into a framework where the framework could access and sweep the phishing site and by utilizing the calculation, it will add new suspicious watchwords to the database. The framework utilizes ML innovation to add new watchwords to the database.

Student performance Prediction is a method for foreseeing an understudy's presentation dependent on his/her past marks. This additionally makes the student know whether he/she is in a situation to arrive at his/her normal or expected marks or not.  On the off chance that this model shows that he/she needs to improve then that student can get ready more for that semester with the goal that he/she can arrive at their normal score. This venture helps the students in improving their exhibition. Presently, Machine learning is one of the most developing and creating dialects nowadays and in this task, we went to utilize ML, some classification algorithms and python.

The speech emotion recognition is one of the major python mini projects which will sort the people’s speech of emotions. The use of the project is can be viewed in call centers where companies record the speech pattern of the customers. The employees of the different companies cater to the needs of their customers and improve accordingly. The project requires knowledge over basic python language.

It is a disease which is a disorder in the nervous system. Parkinson’s disease affects the movement of the human body. In today’s world, around 1 million people are suffering from this disease. This is a disorder which produces neurodegenerative dopamine-producing neurons in the brain. The following system will detect Parkinson’s symptoms in the human body. The project will be made by a new machine learning algorithm called the XGBoost.

An intelligent piece of software which is capable of communicating and gives voice instructions is known as Chatbox. Making a Chatbox is not easy at all as it works on various machine learning concepts. Nowadays, Chatbox has become one of the important parts of machines as it enables a user to communicate directly to the machine. Interaction with the machine consists of voice instructions that the machine can understand. There are basically two types of Chatbox: -

Introduction

Chatbots are very useful for business associations and furthermore clients. Most of the individuals want to talk legitimately from a chatbot as opposed to calling service centres. Facebook discharged information that demonstrated the value of bots. More than 2 billion messages are sent among individuals and organizations month to month. The HubSpot explore tells that 71% of the individuals need to get client service from informing applications. It is a fast method to get their issues understood so chatbots have a splendid future in associations.

Overview of the project

We can easily identify any image immediately after seeing it, but it is hard for the computer to do the same. Nowadays, deep learning has unveiled such difficulties and has facilitated us to build an application which can identify any image. The caption of the image is based on the huge database which will be fed to the system. This machine learning project of image caption generator is implemented with the help of python language. This project will also need the techniques of convolution neural network and recurrent neural network.

Overview of the project

The following project is based on identifying potential customers for a particular product. This project will be implemented using R programming language. For machine learning techniques we will use K-means clustering. The algorithm is used for the project is very essential. Segmentation is the process of dividing customers into various groups for targeted selling. This data analytics project can help sellers a lot in many ways. The sellers can know about the customer’s mentality hence increasing the market for the sellers. 

Machine learning refers to the intelligence which the computer learns by itself to take some decisions on its own. The system which we will work is on the fraud detection project which involves machine learning concepts. Machine learning concepts have now been used in every field such as commerce, medical, banking, insurance, etc. The project aims to detect anything frauds while shopping online, or doing transaction. The system will read the malicious pattern and then display it to the administrator.

Voice assistants come to some degree, in small modules and can play out an assortment of activities subsequent to hearing your command. They can turn on lights, answer questions, play music, put in online requests and do a wide range of AI-based stuff.

We live in an era of personalization, as the days evolve nothing remains static. Through Machine Learning and Data Science nowadays it is possible to suggest, create a product according to the user’s choice and preferences. Personalization, that is recommendations are somewhat static-like Spotify or Netflix uses these algorithms to recommend users what they want to see or listen based on their previously played playlist.

There are further optimizations we can do using data science is to offer more personalized services, such as dynamic pricing used for Movie ticket booking.

Object detection is associated with computer vision and describes a system that can identify the presence of any desired body or object in an image. The output of an object detection process is an image bounded with boxes around the object we want to detect and describe the name of the object. This is one of the most powerful machine learning algorithms.

Autonomous driving cars have an embedded system that can perform object detection in real-time. For instance, when the autonomous car’s system detects a human-shaped body crossing the road the car stops several feet before coming in contact with the human body.

Machine learning is a technique that teaches the computer to perform the actions done by humans or animals (basically learning from experience). Using machine learning you can able to analyse large amounts of data with almost accurate results.

In this machine learning project, you will get an idea about how to use machine learning to predict the coronavirus/COVID-19 outbreak. You can also use the same method to predict other epidemic diseases like malaria, dengue, swine flu, SARS, etc. Recently coronavirus has created a huge impact worldwide by infecting lakhs of people and killing thousands.

Nowadays Machine Learning is used in different domains. From recommending movies to detecting any disease, machine learning is the most talked thing in today's world of technology. Breast Cancer is one of the most common diseases among women. Early diagnosis of such cases can reduce the risk and increases the chance of survival. Diagnosis of the right time can prevent patients from undergoing unnecessary treatments and operations.

Machine learning is a branch of Artificial Intelligence which is used to analyse the data more smartly. It automates the process using certain algorithms to minimize human intervention in the process.

In this machine learning project, we are going to predict the house price using python. This project will help the sellers and buyers to have an overview of the situation so that they can act accordingly.

In this machine learning project, we will use deep learning method to detect the brain tumours with the help of MRI (Magnetic Resonance Imaging) images of the brain.

Brain tumours are two types: malignant and benign. Most of the disease will reach the critical stage if not detected earlier. Timely detection of the disease will help a lot in the treatment process.

The major cause of brain tumours is because of the abnormal growth and uncontrolled cell division in the brain. Pituitary, meningioma and Glioma are some of the common types of tumours.

AI (ML) is one of the clever techniques that have demonstrated promising outcomes in the spaces of order and forecast. One of the growing territories requiring great prescient precision is sports expectation. Because of the enormous money related sums engaged with wagering. What's more, club supervisors and proprietors are making progress toward characterization models. With the goal that they can comprehend and figure techniques expected to win matches. These models depend on various variables associated with the games. The aftereffects of chronicled matches, player execution pointers, and restriction data

Introduction

Neural networks are utilized as a strategy for deep learning, one of the many subfields of artificial knowledge. They have first proposed around 70 years back as a try at reproducing the manner in which the human brain works, yet in a more streamlined structure. Singular 'neurons' are connected in layers, with weights allocated to decide how the neuron reacts when signals are spread through the network.

There are several Machine Learning projects currently available. As it is a leading technology, there are many project ideas based on this field. It will be helpful for engineering students to complete their final year project. Disease prediction from water quality using machine learning is one of the best project ideas. Skyfi Labs will help you with the basic steps of implementing this project. 

Introduction

This article gives guidelines for the project with WEKA software. As we all know data mining is very popular for analysis and modeling, so the article is for student result prediction using data mining. You will definitely learn about What is WEKA software about and How to use it for analysis and prediction. It is very easy to predict the result using WEKA. You can learn new technologies with Skyfi Labs. We provide the best courses for improvement.

Introduction

Today, data Mining becomes highly important among industrial areas and many other organizations. It has become one of the leading technology in today’s world. It helps to analyze the data and predict the result. Data can be dug from a very big database with minimum efforts. Collecting data, computing data, analyzing data are an indivisible area of business methodology. If you want to develop a project using data mining the Skyfi Labs will help you with such an exciting journey.

Seen Jarvis of Iron Man and wanted your own AI, so exploring the world of ML and AI. Well, it is not that in a project you could reach there but when your own computer reaches the capacity to tell about how the message is good or bad about just a statement then you are a step further to it. May be someday this would help to bring Jarvis to you.

This is the Project you should do to practice in Natural Language Processing to move ahead from basic ML libraries like pandas and NumPy to reach a place of Data Scientist.

Introduction

Today, Data Mining becomes highly important among the health care areas along with industrial areas. Mostly data mining is helpful to predict the result by analyzing the data. Collecting data, computing data, analyzing data are an indivisible area of business methodology. As we all know data mining is very popular for analysis and modeling, so the article is for Cancer prediction using data mining. The article focuses on the back end technologies for project implementation. If you are interested in this domain then go through the article. Skyfi Labs helps you to learn more technologies and boost your career.

Introduction

So here is another project idea on data mining or data analysistechnology. It will definitely help to improve your knowledge in data mining field. It analyses the data and uses it to find a similar pattern for prediction and recommendation. So in this article, we will introduce the Restaurant Recommendation System depend on the frame of mind. Data mining system learns from examples of the data that how to partition or classify the data. It helps to discover hidden patterns and insights. If you are interested then Skyfi Labs provides you data mining course too. Check our website for more information.

Project Description

So this article is all about the Restaurant Recommendation System depend on the frame of mind. We will see the basic guidelines for the implementation of the project. The article is helpful for second-year students as their minor academic project. The project focuses on different kinds of mood-wise restaurant recommendations. For example, if the person is happy then he/she will prefer junk food like pizza, burger, etc. If the mood is angry or sad then the person will prefer sweet any more. The article gives back end implementation guidelines for the project.

Human beings tend to learn from previous experiences. The same thing is done nowadays digitally, and the technology is known as Machine Learning. Machine Learning is a branch of Artificial Intelligence or in short AI, the hot cake of today’s technology. Using Machine Learning we can do a lot of stuff, for instance, predicting Bitcoin prices, movie ticket price prediction or people you may know the section on Facebook. Even ML Is used in medical science also. Nowadays, researchers are also able to predict personality using Machine Learning.

Everyone wants their life to be easier with automatic recommendations with customization. Isn’t it cool whenever you purchase your monthly grocery you get recommendations based on what you have saved in your cart? Of course, yes. Here Machine Learning comes into play. Whether it is your favourite music app recommendation what you would like to play next to Netflix or Amazon what you want to see next, Machine Learning works like magic in these cases.

Machine Learning is everywhere. Nowadays, automatic driving cars are into action and being used by lots of people. These automatic driving cars need something that can detect lanes or even moving objects. Here Machine Learning comes into action. Machine learning is used in medical science too. In this case, we will be using deep learning to detect lanes.

As we all know, Machine Learning is ruling the world nowadays. You name it to predict, Machine Learning is there for your predictions. Whether it is Breast Cancer predictions or online grocery recommendation Machine Learning is everywhere and is used by many small to big-sized companies. However, the predictions are not 100% accurate. Depending on which algorithms you have applied, the accuracy varies. Bitcoin Price prediction using Machine Learning can be 67-70% accurate.

Objective:

The objective of this machine learning project is to predict the price of Bitcoins. After the popularity of Bitcoins, it is classified as assets.

Machine Learning has become an integral part of our daily life. It is applied almost everywhere nowadays, whether it be medical sciences or lane detection that is very useful for automatic self-driving cars. Not only that, but machine learning can also be used to prevent road accidents.

Objective:

Tons of accidents occur every day on every highway. So, what about creating a model that will help prevent accidents? We can prevent an accident by creating an accurate model with the help of the patterns of the accidents taking place in urban and rural areas. We can make a cluster of different patterns of accidents and can take necessary safety precautions based on that. But for that, we need an accurate record of road accidents that have taken place in the past few years. According to research, it is stated that residential areas are more prone to accidents. So, we can cluster the areas like that.

Machine Learning is used everywhere. From detecting lanes or detecting objects to real-time food detection, machine learning is the key player in every field nowadays. From tech giants to online shopping apps like Amazon, Flipkart or even music apps, machine learning is used almost in every aspect of today’s life.

Objective:

As the name suggests, the main objective of this project is to detect food in real-time. We will be using CNN and deep learning to detect food images. Deep learning is very useful in image processing, whether it be lane detection, object detection or even food detection. 

When someone borrows some money from someone or some organization, in financial term it is known as loan. Sanctioning a loan isn’t an easy job, there are some procedures on which it depends whether the person or eligible or not. With machine learning, one can predict the person lending money will be a defaulter or not. Machine learning is like a hot cake in today’s technical field. Name something and machine learning has the answer to most of the questions. From detecting face to lane detection to suggesting products, machine learning is used everywhere.

Objective:

The objective of the problem is to pick out which customer will be able to pay the debt and which customer is likely will not be able to pay the debts. Clearly we have to create a classification model here. We have to use algorithms like logistic regression, decision tree or random forest. We need to create a model that is accurate and the error percentage should be less.

Latest Projects based on machine learning