> For the complete documentation index, see [llms.txt](https://grigore-mihaela.gitbook.io/machine-learning/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://grigore-mihaela.gitbook.io/machine-learning/about.md).

# About

### <img src="/files/1gmL68IHV3MWY36WBrwc" alt="" data-size="line"> Who I am

I am currently working in Machine Learning. I have a background in software engineering, research, entrepreneurship.

Formally trained as a software engineer, a programme where I spent 5 years coding various things (operating systems, websites, games, you name it - typical Computer Science track at a Polytechnics university). Spent a few more years afterwards as software developer.&#x20;

Had the chance to pursue a Research MSc in Cognitive Science. After which I decided a PhD and academia is not the suitable environment for me. I co-founded a hardware company. It wasn't a unicorn, nor did we want it to be. We wanted a regular bootstrapped organic growth company.&#x20;

Something was unfolding during these years and it looked impressive. AI was becoming bigger and bigger and I wanted to be a part of that. I returned to studies, to upskill: Maths, Statistics, Machine Learning, productionizing ML and the rest. Through a MSc program, a lot of self-study, personal projects and working in a company that does AI for insurance, I became a junior ML Engineer, but with a rich experience in other fields, which I believe constitutes an advantage.

NLP, Computer Vision, tabular data - I enjoy working on either.&#x20;

Moreover, I choose work conditioned on the product having a benefit to society and the team to be good, passionate, dedicated and fun too.&#x20;

In my spare time, I do 🚴, 🧗, ✈️, 🍝

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[LinkedIn](https://www.linkedin.com/in/mihaela-elena-grigore/) | [GitHub ](https://github.com/mihaelagrigore)| [Kaggle](https://www.kaggle.com/mishki/notebooks) | [Twitter ](https://twitter.com/mishki)
{% endhint %}

{% hint style="info" %}
[My resume (pdf file)](http://mihaelagrigore.info/wp-content/uploads/2022/02/Mihaela%20GRIGORE%20-%20resume.pdf)
{% endhint %}

### Work projects

#### Natural Language Processing R\&D&#x20;

R\&D work for building a search engine for the insurance domain (questions / answers system)&#x20;

My work included reading recent literature (most important research papers and a few books along the way) on state of the art in Information Retrieval and developments in the past few years. &#x20;

![](/files/i13k37CTPIhlUybOB3hj)

I used Transformer based models to build a search engine that would return answers to questions by looking through a corpus of insurance related text.&#x20;

![](/files/LzyM50VKpNgNqKtP6tdC)

#### Computer Vision - production work&#x20;

Choose, fine-tune and customize architecture of Deep Learning models for automatic processing of handwritten information in accident reports.&#x20;

![](/files/cs3Rns7asmJEj1kzIGdV)

Created a software library for generating synthetic images that immitate human handwriting and automatically annotate each word with bounding boxes.&#x20;

![](/files/cU7f1HB9fxnxOPA7YztW)

This allowed us to grow our training set from 3000 images to 300.000 images and train a model with near maximum accuracy on our word splitting task, which was integrated into the production pipeline for automated documents processing.&#x20;

### Some of my personal projects

{% content-ref url="/pages/vvY6XSR59S1CMTppXupw" %}
[Computer Vision | Deep Learning with Tensorflow & Keras (ResNet50, GPU training)](/machine-learning/personal-projects/computer-vision-or-deep-learning-with-tensorflow-and-keras-resnet50-gpu-training.md)
{% endcontent-ref %}

{% content-ref url="/pages/C8zAiywLogbgWd0zC4PZ" %}
[Computer Vision | Convolutional Neural Networks with PyTorch](/machine-learning/personal-projects/computer-vision-or-convolutional-neural-networks-with-pytorch.md)
{% endcontent-ref %}

{% content-ref url="/pages/rzRiOinOisPgN2rbowtg" %}
[Computer Vision | Facial Recognition with Keras, FaceNet, Inception, Siamese Networks](/machine-learning/personal-projects/computer-vision-or-facial-recognition-with-keras-facenet-inception-siamese-networks.md)
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{% content-ref url="/pages/GCo56dm5Lhr2DbdN0AYy" %}
[NLP | Topic modeling on tweets](/machine-learning/personal-projects/nlp-or-topic-modeling-on-tweets.md)
{% endcontent-ref %}

{% content-ref url="/pages/b0RYnxryyPZlcLi75MjE" %}
[NLP | Sentiment analysis of tweets: TextBlob, VADER and Flair](/machine-learning/personal-projects/nlp-or-sentiment-analysis-of-tweets-textblob-vader-and-flair.md)
{% endcontent-ref %}

{% content-ref url="/pages/1JFGSBrOhpUTCC3GWdBw" %}
[Time series | Exploration on Crypto price dataset](/machine-learning/personal-projects/time-series-or-exploration-on-crypto-price-dataset.md)
{% endcontent-ref %}

{% content-ref url="/pages/N0vNzEQG8VAcf7BAtbT7" %}
[Data scraping | Social Media Scraping: Twitter Developer API for Academics](/machine-learning/personal-projects/data-scraping-or-social-media-scraping-twitter-developer-api-for-academics.md)
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{% content-ref url="/pages/OPPZazCwnH1LB5CUIEIh" %}
[Data Scraping | Collecting historical tweets without Twitter API](/machine-learning/personal-projects/data-scraping-or-collecting-historical-tweets-without-twitter-api.md)
{% endcontent-ref %}