Engineering Projects on Machine Learning

Machine Learning is commonly a form of Artificial Intelligence (AI) and comes under it. It lets the software applications to predict the results in an accurate manner without being programmed by any programmer. Machine Learning is capable of learning automatically through the usage of various algorithms and predicts the output values based on the previous input data.

It is an area of study which is assigned specially for the proper understanding and designing of techniques that are capable of learning automatically. These techniques enhance the quality of data for improving the performance of certain groups of tasks.

Why to do Projects on Machine Learning

For technology oriented concepts like machine learning, possession of textbook knowledge alone is not enough. The skill or technology can be mastered only when the students gain practical knowledge in the respective concept. The best way to get practical knowledge in concepts like machine learning is to do Projects on Machine Learning and get hands-on practice or some experience in doing the projects.

By doing Projects on Machine Learning one can get to know about all the possibilities and difficulties existing in doing a real time project which in turn helps the students to get employed in a good organisation after completion of the course. Therefore, the top machine learning project ideas and top machine learning projects for final year with source code are discussed in this article. Professionals who are in search of project ideas can refer to these ideas if interested.

What machine learning project can I do?

Most students doing the projects on machine learning might end up getting the question of “What machine learning project can I do”. Well, the experts of the domains normally suggest the students or candidates to look for some cool, exciting, fun and very simple machine learning project ideas in various sectors like industries, business, research, etc. These projects help to get hands-on practice experience of the skills and knowledge acquired during the entire course program. A set of interesting and innovative machine learning projects for final year students are organised in the article. The balanced approach of the challenges faced by the professionals who are working either as a machine learning engineer or data scientist or deep learning engineer are combined perfectly and presented as the machine learning project ideas.

Machine Learning Projects for Final Year with Source Code

Candidates who are aspiring to work on ML projects as a final year student or as a fresh machine learning engineer professional mostly find it hard to explore the real time interesting project ideas to work on. The most significant aspect is to think about or explore the project ideas which makes you interested and motivated to work on. When selecting the suitable projects on machine learning, it's purely upon the student’s wish to decide about the important aspects like dataset size, complication of the dataset and the dataset domain. The first thing required for doing the best machine learning project is to collect numerous project or research gaps available in the machine learning sector. For that, you have to think, brainstorm and list all the possible or latest project ideas in the machine learning sector. After the collection of the interesting ideas, you can try to do the project which you assume to be most interesting and significant. You can do the machine learning projects by using the source code within them. Doing projects on machine learning with source code certainly adds importance to the students profile. Students doing the machine learning projects with source code also get a chance to know about various other topics like data cleaning, data analytics, deep learning, artificial intelligence etc.

Also read : Machine Learning Projects for Final Year CSE

Significant Steps of a Machine Learning Project

Most machine learning projects have a separate scale and complexity for each other. But the workflow of every machine learning project is found to be very common and the same. Let’s consider the two completely different levels of data science teams like the Data Science team at a start-up & small scale industry and the large Data Science team at a large scale industry like Amazon or Netflix. Both the teams have a same flow of work like the collection of data, preprocessing the collected data and transforming them, training the model, validation of the model and employing the validated model into production. Some of the significant steps existing in all the machine learning projects are listed below:

• Defining the Process of Machine Learning

• Construction of an end-to-end Machine Learning Pipeline

• Employing the Model in Production

Defining the Process of Machine Learning

This is the first and foremost thing done in a machine learning project. One must understand the overall process of machine learning through the proper identification of business use-case, collection of data from various sources, and the identification of machine learning algorithms which can be utilised to solve the issues.

Construction of an end-to-end Machine Learning Pipeline

It is very important to identify the key functions required for the construction of an effective machine learning system for the perfect execution of the machine learning project. This is done through the collection of data from numerous sources, preparation of the collected data for implementation through including the modules for data conversion, and the implementation of the respective machine learning modules.

Employing the Model in Production

This is the third and final step which makes use of the constructed machine learning model in data stores, enterprise systems and other applications. The constructed machine learning model is employed at the production level in industries. The machine learning model gives output either in the form of a report consisting of profit making decisions, or data that are utilised by different systems within the organisation, or a design that is capable of supporting different analytic applications so that more valuable insights can be collected within the organisation.

How to start a machine learning project?

“How to start a machine learning project?” - This is the most widely asked question among the students doing projects on machine learning. Some of the best advice for the final year students doing machine learning projects are:

• Defining and understanding the problem existing in the business

• Acquisition of data

• Preparation of data

• Performing on spot checking of different types of machine learning algorithms

• Selection of the best functioning algorithm and starting the modelling process

• Verification of model and fine tuning it for improved accuracy and performance.

• Deploying the verified model.

• Presenting the developed machine learning model through which the solutions for various business problems are given.

Top Machine Learning Project Ideas

Some of the top machine learning project ideas that every learner of machine learning technology should try are listed below:

• Sentiment Analysis

• Loan Default Prediction

• House Price Prediction

• Stock Price Estimation

• Store Sales Forecasting

Top Machine Learning Projects for Final Year Students with Source Code

Some of the top machine learning project ideas for the final year students are listed below. They are:

• Sentiment Classification from Text Using Deep Learning Algorithm
• Comparative Analysis of ML Algorithms for Drought for Prediction
• Anemia Estimation for Patients Using a ML Model
• Detection of Chronic Kidney Disease using Machine Learning and Deep Learning Algorithms
• Machine Learning Algorithm For Brain Stroke Detection
• Detecting and Characterizing Extremist Reviewer Groups in Online Product Reviews
• Deep Analysis of Autism Spectrum Disorder Detection Techniques.
• Fraud Detection in Credit Card Data using Unsupervised Machine Learning Based Scheme
• Electricity Price Forecasting for Cloud Computing Using an Enhanced Machine Learning Model
• Analysis for Disease Gene Association Using Machine Learning
• A Novel Ensemble Learning Paradigm for Medical Diagnosis With Imbalanced Data
• Construction of Machine-Labeled Data for Improving Named Entity Recognition by Transfer Learning
• Image Reconstruction: From Sparsity to Data-Adaptive Methods and Machine Learning
• A Comparative Approach to Predictive Analytics with Machine Learning for Fraud Detection of Realtime Financial Data
• CLEMENT: Machine Learning Methods for Malware Recognition Based on Semantic Behaviours
• An Experimental Study for Software Quality Prediction with Machine Learning Methods
• Hazard Identification and Detection using Machine Learning Approach
• Predicting Flight Delays with Error Calculation using Machine Learned Classifiers
• Machine Learning based Rainfall Prediction
• Advanced Prediction of Performance of A Student in An University using Machine Learning Techniques
• Novel XGBoost Tuned Machine Learning Model for Software Bug Prediction
• COVID-19 Future Forecasting Using Supervised Machine Learning Models

Conclusion