itsshaikaslam

Aslam Shaik's starred repositories

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

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data-science-interviews

Data science interview questions and answers

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Deep-Learning-In-Production

Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.

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scalable-data-science

Scalable Data Science, course sets in big data Using Apache Spark over databricks and their mathematical, statistical and computational foundations using SageMath.

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DeepLearning-Study

This is repository for DeepLearning Study in Kyung Hee University

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Application_Of_Mask_RCNN_For_CT_Image_Analysis

Application of Masked RCNN for segmentation of brain haemorrhage from Computed Tomography Images

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Artificial-Intelligence-with-Python-Second-Edition

Artificial Intelligence with Python Second Edition, published by Packt

MIT100

course-gitbook

Full Stack Deep Learning Online Course

100

data-science-ipython-notebooks

Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines. https://bit.ly/data-notes

NOASSERTION100

data_science_starter

This is some starter / reference code for those interested in starting data science

100

Deep-Learning-In-Production

Develop production ready deep learning code, deploy it and scale it

100

deep-learning-resources

A curated list of deep learning resources books, courses, papers, libraries, conferences, sample code, and many more.

100

Deep-Learning-Setup

100

dl_with_python

This repository follows Francois Chollet's book, Deep Learning with Python, and implements each chapter in a Jupyter notebook

100

ILearnDeepLearning.py

This repository contains small projects related to Neural Networks and Deep Learning in general. Subjects are closely linekd with articles I publish on Medium. I encourage you both to read as well as to check how the code works in the action.

MIT100