Mayank Jindal's Projects
The contents of this course are essentially the same as those of the corresponding MIT class (The Analytics Edge)In the last decade, the amount of data available to organizations has reached unprecedented levels. Data is transforming business, social interactions, and the future of our society. Will learn how to use data and analytics to give an edge to your career and your life. We will examine real world examples of how analytics have been used to significantly improve a business or industry. These examples include Moneyball, eHarmony, the Framingham Heart Study, Twitter, IBM Watson, and Netflix. Through these examples and many more, we will teach you the following analytics methods: linear regression, logistic regression, trees, text analytics, clustering, visualization, and optimization. We will be using the statistical software R and a spreadsheet software to build models and work with data. The contents of this course are essentially the same as those of the corresponding MIT class (The Analytics Edge). It is a challenging class, but it will enable you to apply analytics to realworld applications.
A curated list of awesome computer vision resources
The course covers Big Data concepts, architecture, and several tools in the Hadoop Ecosystem. The course will cover the theoretical as well as hands-on. The tools covered include Hadoop, Sqoop, Flume, Hive, Pig, and Spark.
Bike sharing systems are a means of renting bicycles where the process of obtaining membership, rental, and bike return is automated via a network of kiosk locations throughout a city. Using these systems, people are able rent a bike from a one location and return it to a different place on an as-needed basis. Currently, there are over 500 bike-sharing programs around the world. The data generated by these systems makes them attractive for researchers because the duration of travel, departure location, arrival location, and time elapsed is explicitly recorded. Bike sharing systems therefore function as a sensor network, which can be used for studying mobility in a city. In this competition, participants are asked to combine historical usage patterns with weather data in order to forecast bike rental demand in the Capital Bikeshare program in Washington, D.C.
Feature exploration for supervised learning
Adapted a Tensorflow implementation of the following paper for handwriting recognition: What You Get Is What You See: A Visual Markup Decompiler (https://arxiv.org/pdf/1609.04938v1.pdf)
Just Rep
Lab Materials for MIT 6.S191: Introduction to Deep Learning
CART and RMFOREST comparison on iris data set
This repository focuses on saving my linkedin articles and stuff that I find "USEFUL" on LinkedIn.
Deep dive into Machine Learning: Edge of Tomorrow ??Random Forest,Logistic Regression,CART, KNN,SVM PCA, KMeans,Learning Curves,Neural Networks,OverFitting,Anomaly Detection,Large Scale ML
ML Projects
This repository contains details about my latest certifications and learning.
Getting my hands dirty with some NLP :NLTK / SPacy / Gensim / Text_Blob / Tm / Topic_Modeling /Deep_Learning
Jupyter notebook and datasets from the pandas Q&A video series
Files for Udemy Course on Algorithms and Data Structures
1.Variables 2. Functions,3.Datatypes,4.conditions,5.Looping and user input,6 File Handling,8 Building a Text Generator,9 Data Analysis with Pandas,10 Numpy,11.Leaflet Webmaps with python and folium,12 Building a website Blocker,13 Building a Website with Python and Flask,14 Building GUI with Tkinter,15 Python for interacting with SQLite and PostGRE SQL,16 Building a desktop database application,17 OOPS,18 Python for image and video Processing,19 Webcam Motion Destector,20 Data Visualization on Browser,21 Webscraping,22 Scraping Real estate property data from web,23 Building a web based financial graph,24 Data Collector Web app with postgreSQL and Flask,25 Building a Geocoder web service
Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano
Deep Learning Summer School + Tensorflow + OpenCV cascade training + YOLO + COCO + CycleGAN + AWS EC2 Setup + AWS IoT Project + AWS SageMaker + AWS API Gateway + Raspberry Pi3 Ubuntu Core
BERT, AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Tensorflow, Mathematics
VIP cheatsheets for Stanford's CS 221 Artificial Intelligence
Intro to TensorFlow tutorial code for DigitalOcean
Predict the fate of the passengers aboard the RMS Titanic, which famously sank in the Atlantic ocean during its maiden voyage from the UK to New York City after colliding with an iceberg.