Introduction to Deep Learning

At this workshop we will move to an interesting topic of Deep Learning. The below a draft agenda:

• A quick talk about meetup group and setting environments (Installation Tenserflow, Keras) Roman
• Introduction to Neural Networks, Linear and Logistic Regression with examples Sahil
• Introduction to Network Architectures and Hyperparameters tuning using Keras Heidi
• A gentle introduction to Advanced Neural Networks Kyle
• Kaggle competitions practice applying Neural Networks Roman

If you would like to share your experience of Deep Learning, please contact me via MeetUp and we will add you to the Agenda.

Please install relevant python packages before the meetup following the installation_tensorflow_keras guide form the below github link. https://github.com/roman79/DSEC/blob/master/deeplearning/installation_tensorflow_keras.txt

The requirements2.txt has the packages from all presenters.

An alternative way will be to use Colaboratory notebooks stored in Google Drive.

https://colab.research.google.com/notebook#fileId=1ZRSZCL5ZTe3Rp_JzYLN_Zdp_ddroU1Eb

Sahil is a graduate student at Maynooth University doing is Masters in Data Science and Analytics. He previously worked at Swaayatt Robots, a self - driving car startup. He is currently working in visualization of big data.

Heidi just started working as a machine learning engineer at One15digital, a small Irish startup. Before, I worked as a Web developer and Site Reliability Engineer for Symantec.

Kyle is the Chief Innovation and Data Officer for an American stratup in the EdTEch space. I also teach Machine Learning @ Scale in the Master of Information and Data Science program at UC Berkeley - focusing on parallelizing ML algorithms using Map/Reduce and Spark. I have an artistic bent to just about everything.

Roman Golovnya is the Data Engineer at The Eclair Group. The Eclair Group is a fast growing automation and AI start-up. Prior to that he worked in IT and Financial Services companies. In a free time, he organizes this meetup group, shares his knowledge and participate in Kaggle competitions.