Request for proposal
  • Facebook
  • Twitter
  • Youtube
  • Instagram
  • Linkedin
  • Clutch
  • Github
  • Pangea
  • Behance
Request for proposal
  • Company
    • About Us
    • FAQ
  • Services
    • Discovery phase
    • Mobile Application Development
    • Web Development
    • Quality Assurance
    • UI/UX design
    • Data Science and Big Data Analytics Services
    • Artificial Intelligence and Machine Learning Services
    • Software Development Services for Startups
    • IT System & Software Integration Services
  • Industries
    • Healthcare
      • Custom Telemedicine Application Development Services
      • Custom mHealth Apps Development Services
      • Medical Device Software Development
    • Education
      • E-learning Software Development Services
      • LMS Development Services
      • School Management Software Development Company
    • Logistics
    • Fintech
      • Banking Software Development
      • Trading Software Development Services
    • Real Estate
      • HOA Management Software Development
      • MLS Software Development Services for Real Estate
      • IDX Software Development and Integration
      • Property Management Software Development
  • Technologies
    • Flutter
    • Python (Django)
    • .NET core
    • Node. JS
    • ReactJS
    • React Native
    • Custom iOS App Development Services
    • Custom Android Application Development Services
  • Success Stories
    • Reviews
    • Case studies
  • Work at Inoxoft
    • Vacancies
    • News & Events
    • Who we are
    • Career
    • AcademyX Courses
    • Benefits
  • Insights
    • Blog
    • White papers
  • Contacts
  • Facebook
  • Twitter
  • Youtube
  • Instagram
  • Linkedin
  • Clutch
  • Github
  • Pangea
  • Behance
  • Company
    • About Us
    • FAQ
  • Services
    • Discovery phase
    • Mobile Application Development
    • Web Development
    • Quality Assurance
    • UI/UX design
    • Data Science and Big Data Analytics Services
    • Artificial Intelligence and Machine Learning Services
    • Software Development Services for Startups
    • IT System & Software Integration Services
  • Industries
    • Healthcare
      • Custom Telemedicine Application Development Services
      • Custom mHealth Apps Development Services
      • Medical Device Software Development
    • Education
      • E-learning Software Development Services
      • LMS Development Services
      • School Management Software Development Company
    • Logistics
    • Fintech
      • Banking Software Development
      • Trading Software Development Services
    • Real Estate
      • HOA Management Software Development
      • MLS Software Development Services for Real Estate
      • IDX Software Development and Integration
      • Property Management Software Development
  • Technologies
    • Flutter
    • Python (Django)
    • .NET core
    • Node. JS
    • ReactJS
    • React Native
    • Custom iOS App Development Services
    • Custom Android Application Development Services
  • Success Stories
    • Reviews
    • Case studies
  • Work at Inoxoft
    • Vacancies
    • News & Events
    • Who we are
    • Career
    • AcademyX Courses
    • Benefits
  • Insights
    • Blog
    • White papers
  • Contacts
  1. Home
  2. Blog
  3. https://inoxoft.com/blog/innovative-machine-learning-projects-in-python-from-inoxoft-students/Innovative Machine Learning Projects in Python from Inoxoft Students

Request for proposal




    Please share with me NDA in advance.
    Please prove you are human by selecting the Flag.

    Innovative Machine Learning Projects in Python from Inoxoft Students

    Innovative Machine Learning Projects in Python from Inoxoft Students

    Pub: Sep 09, 2021•Upd: Jan 20, 2022
    image
    Written by
    Nazar Kvartalnyi
    COO at Inoxoft, former .Net Software Engineer

    Have a project in mind?

    Let’s get in touch!
    Table of contents
    • Python Machine Learning Projects
    • Covid-19 X-ray detection model
    • Poem Analyzer
    • Car Price Predictor
    • Inspiring Machine Learning Projects
    • Conclusion
    l

    Data is the foundation of modern companies, big and small, and being able to work with data is essential to a steady career as a software developer. The promise of learning programming in a “Data-Focused” way means that as long as customers and users are generating data, you can be gainfully employed helping them unleash that data’s potential for their businesses.

    So, a few months ago Inoxoft organized a course “Data-Focused Programming (with Python, AI/ML)”, mentored by our CTO, Brad Flaugher. A 10-week course covered the full stack of technologies available to the modern programmer, with a specific focus on long-supported and much-loved open-source technologies like Python, C, and UNIX.

    To finish the course students had to create innovative machine learning projects and now want to share with you a couple of them.

    Python Machine Learning Projects

    Looking for Dedicated Team?
    Request for proposal

    We didn’t give any ideas of machine learning projects for students, but guided them and hinted at what was going to be innovative these days. They created each of these models from scratch: out of sheer interest and smart pursuit of ML technology. And on a variety of interesting topics: from Covid related projects to ml projects connected to price prediction.

    Covid-19 X-ray detection model

    One of the most relevant and useful machine learning projects was the attempt to create a Covid-19 detection model. But let’s start with the basics: what is object detection? How does it work? And what for? Object detection is a subfield of a computer vision technique that allows us to identify and locate objects in an image or video. Application includes:

    • Autonomous and Assisted Transportation (automated fine issuing)
    • Medical imagery analysis
    • Sports performance tracking and analysis
    • Agriculture monitoring
    • Retail and manufacturing support
    • Crowd control and face recognition
    • Military use

    The goal of the object detection model is to output the bounding boxes, the class of the bounding boxes, and the probability score for that prediction.

    There are three archetypes of Meta Architectures of object detection model.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    • SSD – a model that is based on classification as it analyzes the whole image at once, trying to indicate if there is an object.
    • Faster RCNN – tends to be more on the side of classification due to its architecture: it scans an image and classifies each of them.
    • R- FCN – a mix of both.

    The model itself

    The plan was to do a model that detects and localizes Covid-19, to help doctors to provide a quick and accurate diagnosis. First of all the team classified and detect different categories of pictures.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    Currently, Covid-19 can be diagnosed via PCR test, but the problem with this method is that it takes from a few hours to a few days to detect the virus’s genetic material and receive results. On the other hand, there is a possibility to use an X-ray that potentially can give a result within a few minutes. There are a lot of guidelines that help radiologists differentiate Covid from other viruses. Moreover, other doctors can also take advantage of X-rays to localize the disease.

    The model works in a way that you can upload an (X-ray) image, the model recognizes the class of the image and gives results based on the picture (e.g. Negative/ 38% typical pneumonia, 22% – indeterminate).

    Challenges the team faced:

    • Small dataset (6334 images)
    • Problematic images in the dataset (blurred, exposed, images with foreign objects)
    • The most wanted (Covid related) atypical class had the smallest percentage of all the images in the dataset

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    The team tried the following approaches to see what they can get from such a data set:

    • TensorFlow Object Detection API (with all the benefits it can offer, the particular approach didn’t give high accuracy)
    • Keras, CNNs

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    The team trained the model on the data set and got 47% of accuracy (see the e.g) and used a pre-trained model (VGG19 – Visual Geometry Group)

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    Poem Analyzer

    Among other machine learning projects in python was the one that aimed to analyze poems. The team created a couple of models.

    The first one predicts one or several topics which were addressed in the poem.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    The second model predicts the year the poem was written. The topic model gives about 50% accuracy. The year model has a mean absolute error of 26 years. How does it work?

    • User types the title and text of the poem

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    • After submitting it, the user receives prediction results

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    What the process looked like? Steps included

    • Data sources
    • Dataset creation steps
    • Websites scraping
    • Data consolidation
    • Data merging

    After scraping the websites, the team merged collected data, cleared data from NaN’s, and removed duplicated rows from the dataset. All the copies of poems were removed and all similar labels were united. The same labels led to the unified names. E.g.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    So, among the labels, the team got 153 labels from 281 poems.

    Initial dataset lookup included

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    Also, the team took specific text into consideration: the max length was set to 150 words, shorter texts were dropped and longer – cut.

    Preprocessing

    To fit text to the model there is a need to convert it to numbers. The following steps are needed to get the result:

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    1. Tokenization- the process of converting text into separate elements (called tokens).

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    2. Removing useless words (“stop” words) that have no value and serve only to connect the words that make sense. E.g.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    3. Lemmatization means treating different forms of words as a single word. E.g.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    4. Decontraction is the process of transition from short forms to the full ones in order to unify them. E.g.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    5. Text to sequences. The team used a method of Tensorflow tokenizer to create a dictionary of all used words and labeled them. E. g.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    6. Padding is the process of replacement of the missing words with 0

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    As we mentioned before, one of the machine learning project ideas was to create a model that makes year predictions by author and label as well. To reach accurate predictions, the team tried different approaches.

    The first model:

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    In the second model, the team changed encoding what led to a better result of mean absolute error.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    Then an embedding layer of categorical data was added and the mean absolute error was changed again.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    The team took an average result of embedded text data and embedded categorical data, so the result was 22 years.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    As the result, the final structure looked like this:

    https://inoxoft.com/app/uploads/2021/09/5-copy-17@2x-80-min.jpg

    Car Price Predictor

    This was one of the most innovative ml projects. The goal was to predict car prices based on the image and/or other information about the car. The project itself went through most major stages of the ML pipeline: data collection, data cleaning, data analysis, model selection, model training, and preparing the model for deployment.

    Data was collected from the source by web scraping using the Beautiful Soup library. Collected data include an image, brand, model, price, mileage, fuel type, transmission type, the year, the car was made. A total of over 15 000 pages were scraped and info was collected from about 146 814 cars.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    Sample of collected data

    Images cleaning included the process of filtering out images from the dataset that are not car exterior was used pre-trained VGG16 model, which was fine-tuned on a subset of data (64 car images and 64 not car images)

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    To train a model you need the images with the outer (external) look of the whole machine the images where the interior or the separate part is named “not car images” So in the example, you can see correct classifications – green, incorrect – red.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    The example of images that were classified as “not car” and removed from the dataset.

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    Model training

    Most popular ML algorithms were applied for tabular data. Metric used – mean absolute error (MAPE) Baseline – one-parameter model (return median for all inputs) Baseline mape – 74% (all that gives lower result means it is useful).

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    The best results for car price prediction based on the image were achieved using the pre-trained VGG16 model (MAPE = 35 %).

    Model predictions

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    Predicted vs real price

    Innovative Machine Learning Projects from Inoxoft Students | Inoxoft.com

    Real price vs Predicted price

    Inspiring Machine Learning Projects

    Inoxoft is a software development company offering clients from the USA, Canada, Israel, Norway, and other countries our big data analytics services that can help to get valuable insights from data and apply effective solutions or to produce interesting machine learning projects.
    Our team has expertise in

    • Predictive Analytics
    • Sales prediction
    • Pricing analytics
    • Marketing optimization
    • Natural Language Processing

    If you search for a custom solution, hire Ukrainian software developers to receive the best quality services and enjoy pleasant results.

    Learn more: How to outsource machine learning?

    Conclusion

    Looking for Dedicated Team?
    Request for proposal

    That was a list of impressive machine learning projects completed by our students who created each of these models from scratch. When it comes to improving skills and building a career in software development, we believe that it is important to turn theoretical knowledge into a practical experience by working on your own project. What’s even better is to do it with mentorship by an expert. We are so proud of all our students who did a great job with their projects!

    Visit our website to get the latest news on our courses and exciting projects we are working on!

    How useful was this post?

    Average rating 5 / 5. Vote count: 8

    No votes so far! Be the first to rate this post.

    Share it with your friends!
    ShareShareShare

    Subscribe to blog

    Top 5 posts
    What is Mobile Banking? Advantages and Disadvantages of Mobile Banking
    What is Mobile Banking? Advantages and Disadvantages of Mobile Banking
    7 Software Development Models Comparison: How to Choose the Right One?
    7 Software Development Models Comparison: How to Choose the Right One?
    Gradient Boosting Classifier – Inoxoft
    Gradient Boosting Classifier – Inoxoft
    Reasons Why to Use Predictive Analytics in Retail and eCommerce
    Reasons Why to Use Predictive Analytics in Retail and eCommerce
    How to Design a Web Application Architecture: Components, Models and Types
    How to Design a Web Application Architecture: Components, Models and Types
    You may also like
    Financial Services Technology Trends in 2021
    Financial Services Technology Trends in 2021
    Jan 05, 2022
    Automation of financial processes
    Automation of financial processes
    Jan 05, 2022
    What is the Difference Between Data Science and Data Analytics: Complete Comparison
    What is the Difference Between Data Science and Data Analytics: Complete Comparison
    Dec 16, 2021
    Best Practices on User Profile Design with Examples
    Best Practices on User Profile Design with Examples
    Dec 13, 2021
    Advantages And Disadvantages Of Flutter App Development
    Advantages And Disadvantages Of Flutter App Development
    Dec 06, 2021

      CONTACT US

      If you have any questions, feel free to contact us.

      image
      Viktoriya Khomyn
      Head of Engagement




      Please prove you are human by selecting the Heart.
      Attach a file

      Top-rated software development company

      180+Experts

      7+Years on the market

      150+Happy clients

      200+Happy Projects

      70%Startups

      30%Existing businesses

      What happens next?
      • Our representative gets in touch with you within 24 hours.
      • We delve into your business needs and our expert team drafts the optimal solution for your project.
      • You receive a proposal with estimated effort, project timeline and recommended team structure.

      Microsoft

      Clutch

      Istob

      image
      • Kulparkivska St, 59, Lviv, Ukraine, 79015
      • 1601 Market Street, 19th Floor, Philadelphia, USA, PA 19103
      • 3 Hanehoshet St, Building B, 7th floor, Tel Aviv, Israel, 6971068
      • contact@inoxoft.com
      Menu
      • About Us
      • Case studies
      • Reviews
      • Vacancies
      • News & Events
      • Who we are
      • Career
      • Benefits
      • Blog
      • Knowledge Base
      • Scholarship
      Services
      • Discovery phase
      • Mobile Application Development
      • Web Development
      • Quality Assurance
      • UI/UX design
      • Data Science and Big Data Analytics Services
      • Artificial Intelligence and Machine Learning Services
      • Software Development Services for Startups
      • IT System & Software Integration Services
      Industries
      • Healthcare
      • Real Estate
      • Education
      • Logistics
      • Fintech
      Technologies
      • Flutter
      • Python (Django)
      • .NET core
      • Node. JS
      • ReactJS
      • React Native
      • Custom iOS App Development Services
      • Custom Android Application Development Services
      • Terms Of Use
      • Privacy policy
      • Sitemap
      • Facebook
      • Twitter
      • Youtube
      • Instagram
      • Linkedin
      • Clutch
      • Github
      • Pangea
      • Behance
      © 2022 Inoxoft, All rights reserved

      Contact us

        Have a project? Feel free to call, send us an email or complete the enquiry form.




        Please share with me NDA in advance.
        Please prove you are human by selecting the Tree.