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| <style type="text/css" media="screen"> | ||
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| <meta charset="UTF-8"> | ||
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | ||
| <title>Muhammad Fakhar's Blog</title> | ||
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| <h1>404</h1> | ||
| <p><strong>Page not found :(</strong></p> | ||
| <p>The requested page could not be found.</p> | ||
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| <body> | ||
| <h1>Hi,</h1> | ||
| <p>I am Muhammad Fakhar, a Computer Science student, mainly focused in Data Science and Machine Learning.</p> | ||
| <p>As a Machine Learning practitioner, I have been writing posts and blogs on Data science and ML, here too.</p> | ||
| <p>Thank you for visiting my blog page. I hope you enjoy my articles!</p> | ||
| <p>Thank you.</p> | ||
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| <h1>End-to-End Projects</h1> | ||
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| <h2><a href="https://github.com/fakhar-iqbal/MachineryPriceEstimator_End_to_End_Project">Machine Price Prediction</a></h2> | ||
| <p>In this app, I implemented Random Forest model to generate the price of Machinery based on previous auction data.</p> | ||
| <img src="/images/first.png" alt="First Image"> | ||
| <img src="/images/second.png" alt="Second Image"> | ||
| <img src="/images/third.png" alt="Third Image"> | ||
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| <h2><a href="https://github.com/fakhar-iqbal/Student_Performance_Predictor_End_to_End_Project">Students Performance Predictor</a></h2> | ||
| <p>In this app, I implemented the model to predict the maths score for students based on their profiles.</p> | ||
| <img src="/images/student.png" alt="Student Image"> | ||
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| <h2>Journey with fastai Library</h2> | ||
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| <h3>Computer Vision</h3> | ||
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| <h4>Images Regression</h4> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/blob/main/ComputerVision/ImagesRegression.ipynb">Practice 1: Centre of Head</a></h5> | ||
| <p>In this model, I implemented images regression, to find the coordinates of the centre of the head. It uses MSELoss.</p> | ||
| <img src="/images/regression.png" alt="Regression Image"> | ||
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| <h4>Sinlge Label Classification</h4> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/tree/main/ComputerVision/Dog_vs_CatApp.ipynb">Practice 1: Dog vs Cat Classifier</a></h5> | ||
| <p>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!</p> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/tree/main/ComputerVision/PlayerClassifier.ipynb">Practice 2: Player Classifier</a></h5> | ||
| <p>I made a computer vision model, hosted in gradio on huggingfaces, which differs between two categories of people. Ronaldo and Messi. Funny!</p> | ||
| <img src="/images/messi.png" alt="Messi Image"> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/tree/main/ComputerVision/BearClassifierPrototype%20.ipynb">Practice 3: Bear Detector</a></h5> | ||
| <p>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.</p> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/blob/main/ComputerVision/DigitClassifierNNfromScratch.ipynb">Practice 4: MNIST Digits Classification</a></h5> | ||
| <p>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.</p> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/blob/main/ComputerVision/PetBreedsNN.ipynb">Practice 5: Pet Breed Classification</a></h5> | ||
| <p>In this model, I implemented classifying between 37 different cats and dog breeds. This uses softmax activation function, and CrossEntropyLoss.</p> | ||
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| <h4>Multi-Label Classification</h4> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/blob/main/ComputerVision/MultiLabelClassification.ipynb">Practice 1: Predicting Multipple classes</a></h5> | ||
| <p>In this model, I predicted multiple classes present in the picture. This uses sigmoid activation function and BCELossWithLogits loss.</p> | ||
| <img src="/images/multilabel.png" alt="MultiLabel Image"> | ||
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| <h2>Tabular Data</h2> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/blob/main/Collab_filtering_TabularData/CollaborativeFiltering(onMovies).ipynb">Practice 1: Movies Prediction/Collaborative Filtering</a></h5> | ||
| <p>In this collaborative filtering, I worked on movies dataset, to predict the movie for a user based on his reviews.</p> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/blob/main/Collab_filtering_TabularData/TabularDataModel.ipynb">Practice 2: Price Prediction from previous auctions</a></h5> | ||
| <p>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)</p> | ||
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| <h2>Natural Language Processing</h2> | ||
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| <h5><a href="https://github.com/fakhar-iqbal/FastaiImplementations/blob/main/NLP/LanguageModel_NLP_final.ipynb">Practice 1: Generating text for movie reviews/ Classifying the reviews</a></h5> | ||
| <p>In this Language Model, I predicted the text to write the reviews for movies. Also, I classified them as positive review or negative review.</p> | ||
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