48 skills found · Page 1 of 2
chadi0x / TheBigBrotherThe Big Brother V4.0 is a weaponized OSINT platform featuring username enumeration (473+ platforms), quad-vector visual intelligence, Sky Radar tracking, crypto wallet analysis, SSL intelligence, digital footprint reconstruction, EXIF extraction, advanced dorking, and network reconnaissance.
DPIRD-DMA / Building RegulariserPython library for cleaning and regularising building footprints in geospatial data, aligning edges to principal directions and simplifying polygons for more accurate analysis.
H2Cyber / VolDiffVolDiff: Malware Memory Footprint Analysis based on Volatility
taylorwilsdon / Reddactedreddacted lets you analyze & sanitize your online footprint using LLMs, PII detection & sentiment analysis to identify anything that might reveal personal info you may not want correlated with your anonymous profile
Kcisti / Bat Security ToolkitAutomated Network Reconnaissance and OSINT framework. Streamlines IP tracking, geolocation, and digital footprint analysis in a modular Python environment.
FutTrader / Footprint SystemA footprint reversal system to be used inline with your market structure analysis.
techenthusiast167 / OSINTMAILER A robust Python-based OSINT tool designed for validating and investigating email addresses across social media platforms and known data breaches, enhancing threat intelligence and digital footprint analysis.
techenthusiast167 / DeepSearch DeepSearch is a powerful Python-based OSINT utility that leverages Google's advanced search operators to perform comprehensive digital footprint analysis.
Akajiaku11 / Carbon Footprint Analysis And Emission ForecastingThis project is a Python-based tool for analyzing carbon emissions and forecasting future trends. It uses synthetic data to simulate historical emissions and applies ARIMA (a time series model) and Linear Regression (a machine learning model) to predict future emissions
saezlab / TranscriptutorialThis is a tutorial to guide the analysis of RNAseq dataset using footprint based tools such as DOROTHEA, PROGENY and CARNIVAL
srlcarlg / Srl Ctrader IndicatorsOrder Flow Ticks, Volume/TPO Profile, Weis & Wyckoff System and more for cTrader trading plataform!
techenthusiast167 / INFOFINDER PROA comprehensive Python-based OSINT (Open Source Intelligence) tool for email and phone number verification with breach detection, social media lookup, and digital footprint analysis capabilities.
Open-ET / Flux Data FootprintFootprint estimation and analysis for eddy covariance flux tower data
Aghoreshwar / Awesome Customer AnalyticsCustomer analytics has been one of hottest buzzwords for years. Few years back it was only marketing department’s monopoly carried out with limited volumes of customer data, which was stored in relational databases like Oracle or appliances like Teradata and Netezza. SAS & SPSS were the leaders in providing customer analytics but it was restricted to conducting segmentation of customers who are likely to buy your products or services. In the 90’s came web analytics, it was more popular for page hits, time on sessions, use of cookies for visitors and then using that for customer analytics. By the late 2000s, Facebook, Twitter and all the other socialchannels changed the way people interacted with brands and each other. Businesses needed to have a presence on the major social sites to stay relevant. With the digital age things have changed drastically. Customer issuperman now. Their mobile interactions have increased substantially and they leave digital footprint everywhere they go. They are more informed, more connected, always on and looking for exceptionally simple and easy experience. This tsunami of data has changed the customer analytics forever. Today customer analytics is not only restricted to marketing forchurn and retention but more focus is going on how to improve thecustomer experience and is done by every department of the organization. A lot of companies had problems integrating large bulk of customer data between various databases and warehouse systems. They are not completely sure of which key metrics to use for profiling customers. Hence creating customer 360 degree view became the foundation for customer analytics. It can capture all customer interactions which can be used for further analytics. From the technology perspective, the biggest change is the introduction of big data platforms which can do the analytics very fast on all the data organization has, instead of sampling and segmentation. Then came Cloud based platforms, which can scale up and down as per the need of analysis, so companies didn’t have to invest upfront on infrastructure. Predictive models of customer churn, Retention, Cross-Sell do exist today as well, but they run against more data than ever before. Even analytics has further evolved from descriptive to predictive to prescriptive. Only showing what will happen next is not helping anymore but what actions you need to take is becoming more critical. There are various ways customer analytics is carried out: Acquiring all the customer data Understanding the customer journey Applying big data concepts to customer relationships Finding high propensity prospects Upselling by identifying related products and interests Generating customer loyalty by discovering response patterns Predicting customer lifetime value (CLV) Identifying dissatisfied customers & churn patterns Applying predictive analytics Implementing continuous improvement Hyper-personalization is the center stage now which gives your customer the right message, on the right platform, using the right channel, at the right time. Now via Cognitive computing and Artificial Intelligence using IBM Watson, Microsoft and Google cognitive services, customer analytics will become sharper as their deep learning neural network algorithms provide a game changing aspect. Tomorrow there may not be just plain simple customer sentiment analytics based on feedback or surveys or social media, but with help of cognitive it may be what customer’s facial expressions show in real time. There’s no doubt that customer analytics is absolutely essential for brand survival.
srlcarlg / Srl Python IndicatorsOrder Flow Ticks, Volume/TPO Profile, Weis & Wyckoff System and more for Python with mplfinance/plotly!
Bushell-lab / Ribo SeqAnalysis pipeline for Ribosome footprinting data
nf-core / RiboseqPipeline for the analysis of ribosome profiling, or Ribo-seq (also named ribosome footprinting) data.
saezlab / FootprintsAnalysis code for "Perturbation-response genes reveal signaling footprints in cancer gene expression"
BlockchainLabs / AeonAbout: AEON was launched on 6.6.2014 at 6:00 PM UTC, with no premine or instamine. AEON is for people who want to pay and live freely, who want to be part of the cryptocurrency revolution and want to try something new. It is based on the CryptoNote protocol and uses the CryptoNight-Lite[1] algorithm, and features: - True anonymity & data protection - Untraceable payments uses ring signature - Unlinkable transactions with random data by the sender - Blockchain analysis resistant - CPU/GPU mining, ASIC-resistant Roadmap April 26, 2015 - new roadmap announced Mobile-friendly PoW and block time (released) GUI wallet (in progress) 32-bit and ARM support (released, but requires low memory footprint below) Low memory footprint (in progress) Signature trimming Blockchain pruning (test release available) Multisig and payment channels (instant payments) Development Team: Lead developer: smooth Release engineering, Q/A, support: Arux Other roles: open (PM smooth) Original developer (as Monero fork): anonymous Bounties: None currently open. You can send donations for the AEON bounty fund and development. Code: AEON address: WmsSWgtT1JPg5e3cK41hKXSHVpKW7e47bjgiKmWZkYrhSS5LhRemNyqayaSBtAQ6517eo5PtH9wxHVmM78JDZSUu2W8PqRiNs View Key: 71bf19a7348ede17fa487167710dac401ef1556851bfd36b76040facf051630b Specifications: PoW algorithm: CryptoNight-Lite[1] Max supply: ~18.4 million[2] Block reward: Smoothly varying using the formula (M−A) / (218) / (1012) where M = 264 −1 and A = supply mined to date.[3] Block time: 240 seconds[3] Difficulty: Retargets at every block RPC-bind-port: 11180 P2P-bind-port: 11181 Downloads: Current release 0.9.6.0 (source code, 64 bit Windows binaries) bootstrap for linux-x64 (by community member Phantas 2016-03-10) bootstrap for Windows-x64 (by community member Phantas 2016-03-11) bootstrap for OS X (by community member sammy007 2015-08-08) GUI for Windows 0.2.3 (by community member h0g0f0g0, src.zip, sha1) Instructions to compile on Windows (provided by community member cryptrol): see bottom of this post Recommended: Use caution with community-provided downloads, check reputation and scan for malware Recommended: Use the --donate option when starting the daemon to donate a portion of your computer power to support the project and the network Links & Resources: Trading: - Bittrex - AEON/BTC - Cryptopia - AEON/BTC (also has DOGE and LTC pairs) - OTC thread - AEON/XMR - Speculation thread (moderated by americanpegasus) Pools: - http://52.8.47.33:8080 - Arux's personal pool (2% fee) - http://98.238.231.31:9000 - The Cryptophilanthropist (2% fee) Block Explorers: - Chainradar - Minergate Community: - Reddit - Steem - Twitter - IRC channel #aeon @ Freenode (Webchat Link) Dead Links / Outdated: cryptocointalk white paper Mining: 1. Compile from source code. 2. Launch aeond and wait until it is synchronized. 3. Launch simplewallet --generate-new-wallet=wallet_name.bin --pass=12345 4. Start mining from the wallet using start_mining command Windows Compilation: (provided by community member cryptrol) Compile steps for Windows x64 using MSVC First of all let's get all the tools we need : - Download and install Microsoft Visual Studio Community 2013 (It's a free version of visual studio with some license limitations). You can uncheck the web development tools and SQL tools since you won't use them for building AEON. This will take time to download and install and you will have to reboot upon completion. - Download and install cMake for windows from : http://www.cmake.org/download/ (Win32 install) - Download Boost 1.57 from http://www.boost.org/users/download/ , use the zip or 7zip archive and extract. You can use c:\boost_1_57_0 since this is what I am using for this steps. - Download and install Github for Windows from https://windows.github.com/ (This also includes a Git shell that we will use later). Now the nasty part compile & build time ! - Build Boost : Open a command line and type : Code: > cd c:\boost_1_57_0 > bootstrap.bat > b2 --toolset=msvc variant=release link=static threading=multi runtime-link=static address-model=64 - Open the Git Shell (or Git bash) depending what you downloaded previously and do. Code: > git clone https://github.com/aeonix/aeon.git > cd aeon > mkdir build > cd build > cmake -G "Visual Studio 12 Win64" -DBOOST_ROOT=c:\boost_1_57_0 -DBOOST_LIBRARYDIR=c:\boost_1_57_0\stage\lib .. > MSBuild Project.sln /p:Configuration=release /m You should now find the exe files under build/src/release . Aeon isn't a cryptocurrency. It's a lifestyle. It's about polished perfection, attained by breaking the rules with calculated mastery of the art. It's about respecting history and pushing innovation forward at the same time. It's about more than just math: it's a vision of a world where luxury is the same as entry-level, and the limits are the heavens themselves. If you're just buying Aeon to get rich, don't even bother. Aeon needs more than just the next wave of crypto speculators: we're looking for the truly elite. But if you think you have what it takes to redefine global finance and discover new magnitudes of wealth in the process... Well, Aeon is ready for you. Are you ready for Aeon?
gregh83 / DinoTrackerApp for dinosaur footprint analysis via disentangled variational autoencoder.
