SmartLake is an online community sharing articles about the application of new technology to business problems. We are particularly interested by the application of artificial intelligence, machine learning and blockchain. The name of the site was inspired by the beautiful Geneva lake region where we come from.

Security and data  privacy is our top priority, this is why our site is secured with a proper certificate

Just Launched

The CV and Resume comparison engine powered by machine learning and natural language processing

 The SmartLake comparison engine is totally unique and allows job applicants to fine tune their CV in real-time using a very simple dialogue. It compares not only keywords, but also skills and highlights the differences between the job description and the candidate’s CV. You just have to paste the text of the job and your own CV and the engine is doing the rest. Once done you can navigate and update your CV in order to match jobs more closely.

 

Take a look at the short video.

If you want to access the tool, go to the contact page and send us your request.

Selected SmartLake Posts

Personalizing Client Interaction in Financial Services

Background All financial services providers need more personalized offerings when interacting with clients and especially new clients. As a client I want to get some personalized recommendations on what to do next or which product to choose. Banks and other providers...

Loan Scoring: Analyzing Data with R

Objective Objective of the analysis is to find a potential way to detect or score loans pro actively using a machine learning model. The analysis done in R can be found here: https://rpubs.com/protzetter/557500 A small Shiny application can also be seen below where...

Personalization in Financial Services ( Part I)

Rationale We can see an increasing demand for personalized digital services in financial services. An article from BCG on the topic is helping in understanding the challenges and the opportunities of personalization in banking...

Federated Learning: Sharing and Improving Models

Introduction The WEF has published a very interesting white paper describing various privacy enhancing techniques. You can find the document under...

Onboarding Virtual Assistant for Banking: Adding Product Recommendations

Improving the Banking Onboarding Assistant In a previous article, https://smartlake.ch/on-boarding-virtual-assistant-myths-and-reality/, we have demonstrated how to use a banking virtual assistant to assist client on boarding....

On-boarding Virtual Assistant: Myths and Reality

There is quite a number of myths and legends about virtual assistants. When reading the news and articles, it seems artificial intelligence can learn about everything and then reproduce anything it has learned. This is somewhat true. If it is not trained with business...

Blockchain: Smart Contract for dummies by the Swiss Government

What we can learn from the Legal Framework for distributed ledger technology and blockchain in Switzerland? Couple of days ago the Swiss Federal Council published a report on Blockchain. Interestingly the report focus on the fundamentals of this technology and the way...

Conversational Assistants in Banking: Designing Flexible Dialogues

In the previous article on the same topic https://smartlake.ch/banking-assistant-interaction-made-easy/, I shared a few lessons learned while developing a simple chatbot for client on-boarding and came to the conclusion that technology was not the main challenge, but...

Intelligent Client Management in Banking: Machine Learning Classification at work

Client management and specifically  on-boarding in banking and wealth management is still a tedious and complex process. It typically requires collecting, cleaning and processing of client data, applying a number of more or less automated rules and finally some human...

Natural Language Processing: Resume Comparison Engine (Part 6)

Introduction In the previous 5 articles we have illustrated the usage of Google and AWS NLP APIs. We have also experimented the spacy library to extract entities and nouns from different documents. We have shown how to improve the model using pattern matching function...

Personalization in Financial Services ( Part I)

Rationale We can see an increasing demand for personalized digital services in financial services. An article from BCG on the topic is helping in understanding the challenges and the opportunities of personalization in banking...

Federated Learning: Sharing and Improving Models

Introduction The WEF has published a very interesting white paper describing various privacy enhancing techniques. You can find the document under...

Onboarding Virtual Assistant for Banking: Adding Product Recommendations

Improving the Banking Onboarding Assistant In a previous article, https://smartlake.ch/on-boarding-virtual-assistant-myths-and-reality/, we have demonstrated how to use a banking virtual assistant to assist client on boarding....

On-boarding Virtual Assistant: Myths and Reality

There is quite a number of myths and legends about virtual assistants. When reading the news and articles, it seems artificial intelligence can learn about everything and then reproduce anything it has learned. This is somewhat true. If it is not trained with business...

Natural Language Processing: Experimenting spaCy and updating the model (Part 5)

Introduction In the previous 4 articles we have illustrated the usage of Google and AWS NLP APIs. We have also experimented the spacy library to extract entities and nouns from different documents. We have shown how to improve the modle using pattern matching function...

Natural Language Processing: Experimenting spaCy (Part 4)

Introduction In the previous 3 articles we have illustrated the usage of Google and AWS NLP APIs and experimented the spacy library to extract entities and nouns from different documents. We have chosen to use personal profiles and job description, as this is a common...

Natural Language Processing: Experimenting Entity Recognition ( Part 3 spaCy)

Introduction In the first two articles of the series we have shown how to use the Google NLP andthe AWS Comprehend API to extract words from a person profile and compare it to a job description...

Natural Language Processing: Experimenting Entity Recognition ( Part 2 AWS Comprehend NLP API)

Introduction In the first article of the series we have shown how to use the Google NLP API to extract words from a person profile and compare it to a job description (https://smartlake.ch/natural-language-processing-experimenting-entity-recognition-part-1/). In this...

Natural Language Processing: Experimenting Entity Recognition ( Part 1 Google NLP API)

Introduction Natural language processing is one of the most promising areas of machine learning and artificial intelligence today and the area that is growing the fastest. There are lots of figures out there that are trying to predict the growth of the market, but I...

Blockchain: Smart Contract for dummies by the Swiss Government

What we can learn from the Legal Framework for distributed ledger technology and blockchain in Switzerland? Couple of days ago the Swiss Federal Council published a report on Blockchain. Interestingly the report focus on the fundamentals of this technology and the way...
How to run successful projects:all about people

How to run successful projects:all about people

Some background Since I continue to manage projects and continue enjoying it, I was thinking about what makes a project successful and what are the lessons learned across all these years of project and program management. We can read a lot about Agile and the...

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