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โ€œTorture the data long enough, it will confess to anything.โ€๐Ÿ˜Š
๐Ÿ’ป
โ€œTorture the data long enough, it will confess to anything.โ€๐Ÿ˜Š

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mohd-faizy/README.md

A Data Science Enthusiast | Focused on Solving real-world problem using AI & Machine Learning | Masters Degree in Electronics & Comm. Engg. | ๐ŸŽ“Alumnus: Jamia Millia Islamia

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  • Aims at Bridging the gap between AI Universe and Chip level Universe to get from AI frameworks like TensorFlow into synthesizable RTL, enabling the development of high-performance inference architectures.
  • Iโ€™m currently learning TensorFlow Probability for probabilistic reasoning and statistical analysis

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c Python Pycharm Git GitHub linux Google Colab Jupyter Spyder OpenCV Pytorch tensorflow alt Numpy Pandas scikit_learn alt alt alt alt alt alt alt alt alt alt alt alt alt alt alt alt alt alt alt alt alt alt alt

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  1. Probabilistic Deep Learning finds its application in autonomous vehicles and medical diagnoses. This is an increasingly important area of deep learning that aims to quantify the noise and uncertainโ€ฆ

    Jupyter Notebook 38 25

  2. Finetuning BERT in PyTorch for sentiment analysis.

    Jupyter Notebook 11 5

  3. This Repo contains tools that allow us to import, clean, manipulate, and visualize data โ€”Includes Python libraries, like `pandas`, `NumPy`, `Matplotlib`, and many more to work with real-world datasโ€ฆ

    Jupyter Notebook 4 1

  4. Training a CNN in Keras with a TensorFlow backend to solve Image Classification problems

    Jupyter Notebook 4 2

  5. Machine Learning - - Supervised, Unsupervised, and deep learning. Processing data for features, training models, assess performance, and tune parameters for better performance. In the process, you'โ€ฆ

    Jupyter Notebook 1

  6. Projects : DataScience, Artificial intelligence, Machine learning, Deep Learning

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208 contributions in the last year

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