CV & DS Project List


Below are a list of Computer Vision and Data Science Problems that I have come across and solved. They are well documneted here for beginners to try out along with guidance from solutions I have provided


  • Classification, Deep Learning, Machine Learning Project
    Deep Learning Challenge- 'Tis STILL the season to be jolly'

    You work for a social media platform. Your task is to create a solution using deep learning to discern whether a post is holiday-related in an effort to better monetize the platform.

    Task

    You are given the following six categories. You are required to classify the images in the dataset based on these categories.

    • Miscellaneous
    • Christmas_Tree
    • Jacket
    • Candle
    • Airplane
    • Snowman

    The data folder consists of two folders and one .csv file. The details are as follows:

    • train: Contains 6469 images for 6 classes
    • test: Contains 3489 images
    • train.csv: 3489 x 2

    Submission format

    You are required to write your predictions in a .csv file and upload it by clicking the Upload File button.

    SOURCE: HackerEarth

    Solution: View on Colab


  • Classification, Deep Learning, Machine Learning Project
    Machine Learning Challenge Exhibit A(rt)

    You work for a company that sells sculptures that are acquired from various artists around the world. Your task is to predict the cost required to ship these sculptures to customers based on the informatio...

    Task

    In the pandas dataframe, the following columns are given. Use them to predict the final cost in the test set.

    • Customer Id: Represents the unique identification number of the customers
    • Artist Name: Represents the name of the artist
    • Artist Reputation: Represents the reputation of an artist in the market (the greater the reputation value, the higher the reputation of the artist in the market)
    • Height: Represents the height of the sculpture
    • Widht: Represents the widht of the sculpture
    • Weight: Represents the weight of the sculpture
    • Material: Represents the material that the sculpture is made of
    • Price Of Sculpture: Represents the price of the sculpture
    • Base Shipping Price: Represents the base price for shipping a sculpture
    • International: Represents whether the shipping is international
    • Express Shipment: Represents whether the shipping was in the express (fast) mode
    • Installation Included: Represents whether the order had installation included in the purchase of the sculpture
    • Transport Represents the mode of transport of the order
    • Fragile: Represents whether the order is fragile
    • Customer Information: Represents details about a customer
    • Remote Location: Represents whether the customer resides in a remote location
    • Scheduled Date: Represents the date when the order was placed
    • Delivery Date: Represents the date of delivery of the order
    • Customer Location: Represents the location of the customer
    • Cost: Represents the cost of the order

    The data folder consists of two folders and one .csv file. The details are as follows:

    • train: Contains 6469 images for 6 classes
    • test: Contains 3489 images
    • train.csv: 3489 x 2

    Submission format

    You are required to write your predictions in a .csv file and upload it by clicking the Upload File button.

    SOURCE: HackerEarth

    Solution: View on Colab



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