cme

NDelventhal/cot_reports

cot_reports is a Python library for fetching the Commitments of Trader reports of the Commodity Futures Trading Commission (CFTC). The following COT reports are supported: Legacy Futures-only, Legacy Futures-and-Options Combined, Supplemental Futures-and-Options Combined, Disaggregated Futures-only, Disaggregated Futures-and-Options Combined, Traders in Financial Futures (TFF) Futures-only and Traders in Financial Futures (TFF) Futures-and-Options Combined.

epam/java-cme-mdp3-handler

Java Market Data Handler for CME Market Data (MDP 3.0)

dod38fr/config-model

Perl module to create configuration editor with semantic validation

vincent212/CME-Market-Data-Handler

A minimalist, low-latency, HFT CME MDP3.0 C++ market data feed handler and pcap file reader (MDP 3.0)

databricks-industry-solutions/causal-incentive

Accelerator for customer incentive investment using causal inference techniques

bbcho/risktools-dev

Risk tools for commodities trading and finance

databricks-industry-solutions/customer-er

Translating text attributes (like name, address, phone number) into quantifiable numerical representations Training ML models to determine if these numerical labels form a match Scoring the confidence of each match

johan12345/gcs_python

Graduated cylindrical shell CME model in Python

databricks-industry-solutions/fine-grained-demand-forecasting

Perform fine-grained forecasting at the store-item level in an efficient manner, leveraging the distributed computational power of the Databricks Data Intelligence Platform.

databricks-industry-solutions/multi-touch-attribution

Connect the impact of marketing and your ad spend to sales. Efficiently pinpoint the impact of various revenue-generating marketing activities to understand what works best. Focus on the best-performing channels to optimize media mix and drive revenue.

vincent212/FIX-Order-Routing-Client

FIX order manager client for fix order routing in C++ using QuickFIX engine can be used for Trading Technologies (TT) or CQG and others

databricks-industry-solutions/media-mix-modeling

imandra-ai/cme-mdp

Imandra Modelling Language CME MDP Model

databricks-industry-solutions/segmentation

Create advanced customer segments to drive better purchasing predictions based on behaviors. Using sales data, campaigns and promotions systems, this solution helps derive a number of features that capture the behavior of various households. Build useful customer clusters to target with different promos and offers.

sambacha/CME-iLink3

CME iLINK3 Connectivity

databricks-industry-solutions/real-time-bidding

From display to video, the value of an impression can only be realized if an ad is viewed by a user. Therefore, when using programmatic advertising to buy inventory, it’s important to take viewability into account. In this Solution Accelerator, learn how to predict ad viewability to optimize your real-time bidding strategy.

yiminking/CME-CNN

CME Arrival Time Prediction Using Convolutional Neural Network

databricks-industry-solutions/toxicity-detection-in-gaming

Build a lakehouse for all your gamer data and use natural language processing techniques to flag questionable comments for moderation.

CJuanvip/CMEOptions

Analyze the CME grain options markets in python

databricks-industry-solutions/propensity

Get started with our Solution Accelerator for Propensity Scoring to build effective propensity scoring pipelines that: Enable the persistence, discovery and sharing of features across various model training exercises Quickly generate models by leveraging industry best practices Track and analyze the various model iterations generated

databricks-industry-solutions/wide-and-deep

Build a wide-and-deep recommender with collaborative filters that takes advantage of patterns of repeat purchases to suggest both previously purchased and related products.

LiXiang618/Scrape-Futures-Specs-From-CME

Use futures symbols to search and get their contract specs From CME website

pachterlab/biophysics

Repository for Pachter Lab Biophysics

CME-OS/cme

Campaigns Made Easy - Open Source Email Campaign Sysetm

databricks-industry-solutions/survival-analysis

Survival analysis is a collection of statistical methods used to examine and predict the time until an event of interest occurs. In this Solution Accelerator, learn how to use different survival analysis techniques for predicting churn and calculating lifetime value.

alexpinel/CatView

CME SHARP Active region visualisation tool

Clutchisback1/GIT_THEM

Just a quick and dirty little script import all the github goodies I like to play with.

databricks-industry-solutions/sfdc-byom

astronish16/Cone_Model_for_CME

This repository provides a python code to infer morphological parameters of Coronal Mass Ejection using Cone model given by Xie et al.,2004.

astronish16/DBM

This repository provides the python-based code for Coronal Mass Ejection(CME) arrival forecast using Drag Based Model(DBM).

databricks-industry-solutions/campaign-effectiveness

Identifying Campaign Effectiveness For Forecasting Foot Traffic

e-nzym3/nxc_spray

Bash wrapper script to perform timed password sprays using NetExec.

jayeshpandey01/Ekip_Bhaskar_CME_Event

Explore the detection and prediction of Halo Coronal Mass Ejections (CMEs) using Aditya-L1's Solar Wind Ion Spectrometer (SWIS) data. This project processes Level-2 data with Python to develop an early warning system for space weather, validated against the CACTUS database.

npredey/CMEParser

vieee/CME_equity_options_pricer

Professional-grade options pricing and analytics platform with real-time market data, advanced visualization, and multiple option pricing models.