*** I have a degree in Economics (graduated top 5% of my class even though I wasn’t all that serious during my first two years in college). Though I am really good at many things (programming, finance, statistics, history, politics, etc) and also widely read, you can call me an ML Engineer with years of Machine Learning experience both professionally and academically (I have taught machine learning concepts to university students and aspiring machine learning practitioners). 

*** I have years of experience working with the Python Machine Learning stack (TensorFlow, Keras, Pytorch, Scikit-Learn, etc) and I can Machine Learn using R too. Also, I am proficient in using the AWS Machine Learning stack to do Machine Learning and deploy models to production. I have done many projects (mostly off Upwork at my day job) and the projects I have participated comes from a variety of use cases such as computer vision, natural language processing, natural language understanding, deep neural networks, Generative Adversarial Networks (GANS) and time-series machine learning using fundamental RNN’s and its various varieties (GRU, LSTM).

 *** Various other projects I have worked on include classification/regression tasks using the Scikit-Learn Stack and some unsupervised machine learning use cases (clustering and dimensionality reduction) etc. In as much as I don't currently know how to use Google Cloud Platform or Microsoft Azure for Machine Learning, be rest assured that I will sure learn those two in the future because I really do love learning new stuff (hey, I am smart which I love telling people haha and I am self-taught Machine Learning practitioner that learned to code in 6 months even though I had no computer science background).