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-I am Muhammad Fakhar, a Computer Science student, mainly focused in Data Science and Machine Learning.
+As a Machine Learning practitioner, I have been writing posts and blogs on Data science and ML, here too.
+Thank you for visiting my blog page. I hope you enjoy my articles!
+Thank you.
+ +In this app, I implemented Random Forest model to generate the price of Machinery based on previous auction data.
+ + + + +In this app, I implemented the model to predict the maths score for students based on their profiles.
+ + +In this model, I implemented images regression, to find the coordinates of the centre of the head. It uses MSELoss.
+ + +I made a computer vision model hosted in gradio, on huggingfaces, in Fastai, which classifies between dogs and cats. Have a look in my repo! Click the title!
+ +I made a computer vision model, hosted in gradio on huggingfaces, which differs between two categories of people. Ronaldo and Messi. Funny!
+ + +In this model, I classified between 3 types of bears, black, teddy and grizzly. With 100% accuracy. This app prototype is also hosted on huggingfaces spaces.
+ +In this model, I just took 2 digits, as provided as Samples in the dataset. I implemented the Neural Network from scratch to classify the single label. This uses softmax activation function and CrossEntropyLoss.
+ +In this model, I implemented classifying between 37 different cats and dog breeds. This uses softmax activation function, and CrossEntropyLoss.
+ +In this model, I predicted multiple classes present in the picture. This uses sigmoid activation function and BCELossWithLogits loss.
+ + +In this collaborative filtering, I worked on movies dataset, to predict the movie for a user based on his reviews.
+ +In this model, based on previous prices of machines on auctions, I predicted the price for new machinery. I used the data from kaggle.(bluebook for bulldozers)
+ +In this Language Model, I predicted the text to write the reviews for movies. Also, I classified them as positive review or negative review.
+ + + + +