ComplyCube offers one of the most advanced and complete platforms in the identity verification and KYC space, helping small, large, and prominent organizations effortlessly meet their AML obligations worldwide.
ComplyCube's mission is to grow trust in the global digital economy by empowering businesses of all sizes to implement slick and resilient verification journeys that increase customer conversions, prevent fraud, and reduce onboarding costs – all without adding unnecessary friction to genuine users.
The all-in-one KYC verification platform is built upon cutting-edge AI, trusted sources, and expert human reviewers, allowing us to offer an extensive and coherent array of checks, including AML & PEP Screening, Document Authentication, Biometric Verification, Multi-bureau Checks, Address Verification, and much more.
Why ComplyCube?
❇️ Trusted by startups and big names alike, including AXA, Lycamobile, and Citi.
❇️ 98% Client onboarding rate, helping you convert more customers and grow your business.
❇️ One-stop solution for everything you need to meet your AML and KYC compliance obligations.
❇️ Global coverage of 220+ countries, 10,000+ document types, and over 3,000 data points from trusted sources and partners worldwide.
❇️ A large set of features and checks, including PEP and Sanctions Screening, Adverse Media Checks, ID Document Verification, Biometric Checks, Liveness Detection, Government Database Checks, Address Verification, and more.
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ComplyCube makes it easy to verify identities and stay compliant with regulations. It helps businesses onboard customers smoothly while following the rules. With simple tools to check identities and manage risks, ComplyCube is a great choice for any company needing to keep things legal and straightforward.
This was one of the most pleasant SaaS integrations I've ever experienced. Simple documentation, quick engagement from Sales all the way to Support. We wanted to launch our product in two countries, then scale to 16 within 4 months. ComplyCube was extremely supportive and provided us with KYC strategy and a platform that's flexible and useful for our business needs. Very pleased!
We've tried several SaaS platforms in the identity verification space, but we were left frustrated with complicated integration steps and not particularly unhelpful support and sales.
ComplyCube (and shoutout to Vic and Lucas) were brilliant from the get-go! The API documentation is rich and easy to follow. Integrations took us a couple of hours and our clients are breezing through the onboarding process keep it up guys!
Based on our record, Scikit-learn seems to be more popular. It has been mentiond 27 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 11 months ago
The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 11 months ago
Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 12 months ago
Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: about 1 year ago
This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
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NumPy - NumPy is the fundamental package for scientific computing with Python