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Achievement: YOLOAchievement: Pull Sharkx2

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Achievement: YOLOAchievement: Pull Sharkx2

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iamarchisha/README.md

Hi there 👋

👋🏽 Hi, my name is Archisha, which is a Sanskrit word derived from the Vedas and it translates to - intensity of sun rays.

🎓 Grad with a Bachelor's of Engineering in Computer Engineering.

🌇 Mumbai Native, with a passion for generative models in computer vision.

📚 I have worked on synthetic data generation, product promotion optimization, built solution for TV content compliance using Deep Learning, customer segmentation and price optimization that helped businesses grow. I have extensive experience with Git, Python, TensorFlow, PySpark and AWS Sage Maker.

💻 As for my future, I hope to one day work as Researcher at Google Brain and work with a diverse team of great minds in the field of Computer Vision.

🏔 In my free time, you can find me either swimming or hiking.

💪🏽 Data Science solution pipeline planning, Computer Vision Research, Deep Learning architecture improving, Mentoring.

Links

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  1. multistep-io-timeseries multistep-io-timeseries Public

    Python script for regression of multivariable LSTM neural network.

    Python 10

  2. mozilla/PRESC mozilla/PRESC Public

    Performance Robustness Evaluation for Statistical Classifiers

    Jupyter Notebook 35 52

  3. Enib Enib Public

    Forked from shintan777/Enib

    A submission to AIDL hackathon 2020

    Python

  4. PSTT PSTT Public

    Python Speech to Text

    JavaScript

  5. JS script to prepare json files for ... JS script to prepare json files for performing object detection on AWS Sage Maker. It needs a csv input containing: image_name with extensions (str), img-height (int) , img-width (int), depth (int), left (int), top (int), width (int), height (int), label (str), label_id (int). This csv can have duplicate image_path value to represent different objects detected in the same image. Only one json for each image_path will be created in the format accepted by AWS Sage Maker. The name of json file must be image_name.json (without .jpg extension, eg: image-1.json).
    1 
    const fs = require("fs");
    2 
    const path = require("path");
    3 
    const csv = require("fast-csv");
    4 
    let megaJSON = {}; //will contain a json of multiple jsons
    5 
    let aws_s3_URL = "<s3-data-url>"; //s3 url
  6. RDScML RDScML Public

    Built as a guide for anyone who is new to data science and machine learning; it provides a detailed guide, that is- from everything about Python, NumPy, Pandas, word2vec, NLTK etc to using these AP…

    Jupyter Notebook 3 13