Pinned Repositories
100-shell-script-examples
Collection of shell scripts found on the internet
ab-framework
Notes and Python scripts for A/B or Split Testing
AnalyticsVidya_Contests
Repository holds all the contests and Hackathons from Analytics Vidya
anonymization-api
How to build and deploy an anonymization API with FastAPI
appliedml_workshop_dhs_av_2019
Content for Applied ML Workshop @ DataHack Summit 2019
art_of_data_visualization
The art of effective visualization of multi-dimensional data
churn-model
deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
gender_classifier_mlapp_with_streamlit
health-indices
A unified collection of health indices and health indicators eg: bmi, bai,corp index etc..
nk6june's Repositories
nk6june/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
nk6june/awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
nk6june/BigDataCourse
Materials for the Advanced Data Analysis Techniques with Apache Spark mini-course
nk6june/CategoricalAnalysis
Analysis of Categorical Encodings for dense Decision Trees
nk6june/Coursera-Machine-Learning
Coursera Machine Learning - Python code
nk6june/data-analytics-machine-learning-big-data
Slides, code and more for my class: Data Analytics and Machine Learning on Big Data
nk6june/data-science-ipython-notebooks
Recently updated with 50 new 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.
nk6june/data-science-portfolio
Portfolio of data science projects completed by me for academic, self learning, and hobby purposes.
nk6june/DataScienceResources
Open Source Data Science Resources.
nk6june/Deedy-Resume
A one page , two asymmetric column resume template in XeTeX that caters to an undergraduate Computer Science student
nk6june/Deep-Learning-with-Keras
Code repository for Deep Learning with Keras published by Packt
nk6june/ETL_with_Python
ETL with Python - Taught at DWH course 2017 (TAU)
nk6june/FreeML
Data Science Resources (Mostly Free)
nk6june/image_keras
Building an image classifier using keras
nk6june/instacart-basket-prediction
Kaggle | Instacart Market Basket Analysis🥕🥉
nk6june/introduction_to_ml_with_python
Notebooks and code for the book "Introduction to Machine Learning with Python"
nk6june/julia
The Julia Language: A fresh approach to technical computing.
nk6june/keras
R Interface to Keras
nk6june/learning-social-media-analytics-with-r
This repository contains code and bonus content which will be added from time to time for the book "Learning Social Media Analytics with R" by Packt
nk6june/LightGBM
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
nk6june/mongoEDA
Exploratory Data Analysis using MongoDB
nk6june/ozymandias
Real-time image processing at scale using Kafka and Spark Streaming
nk6june/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
nk6june/resume-1
nk6june/spark-py-notebooks
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
nk6june/spark-r-notebooks
R on Apache Spark (SparkR) tutorials for Big Data analysis and Machine Learning as IPython / Jupyter notebooks
nk6june/tensorflow
TensorFlow for R
nk6june/tensorflow-gpu-install-ubuntu-16.04
Tensorflow GPU install instructions for ubuntu 16.04
nk6june/TimeSeriesAnalysisWithPython
nk6june/Twitter-Sentiment-Analysis-Using-Spark-Streaming-And-Kafka
Twitter Sentiment Analysis using Spark and Kafka