zeeshan75,P MD ZEESHAN SHEIKH,github

100_days_of_ml_code

These are the instructions for "100 Days of ML Code" By Siraj Raval on Youtube

applied-deep-learning-with-keras

Deep Learning examples with Keras.

applied-machine-learning

A step-by-step guide to get started with Applied Machine Learning

awesome-computer-vision

A curated list of awesome computer vision resources

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

background-matting

Background Matting: The World is Your Green Screen

benchmarking-and-mli-experiments-on-the-adult-dataset

Contains benchmarking and interpretability experiments on the Adult dataset using several libraries

bert_telugu_ner

Finding the named entities from the sentences of telugu language trained the model using Googles BERT.

book-deep-learning-applications-with-applications-using-python

Chapterwise code available in the book

collection-of-interview-questions-ml-pdfs

Gathered multiple pdfs regarding interview questions on machine learning and deep learning

computer_vision_notes

Contains image classification object detection(yolo version) segmentation(detectron2) materials(notes, pdfs)

dailycodebase

2 month data structures and algorithmic scripting challenge starting from 20th December 2018 - Coding is Fun! 💯💯 Do it everyday!! Also, Do give us a ⭐ if you liked the repository

darkflow

Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

data-science

:bar_chart: Path to a free self-taught education in Data Science!

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.