Exclusive Event. For those wanting to go deeper into the exploratory data analysis, feature encoding, and applying deep learning utilizing company datasets to achieve industry results. Only a few tickets available.
You will learn:
Basic set-up of Keras
Introduction to Financial Prediction Strategies
Introduction to univariate feature prediction
Introduction to the differences of time series prediction algorithms
A practical coded example of LSTM (Long short term memory) algorithm prediction. You will be able to code this yourself after 1.5 hours.
Your Bootcamp Prep Workshop
This is a preliminary free workshop for the upcoming bootcamp -> Master Applied Data Science Algorithms bootcamp here).
Free ticket here:
Machine learning (ML) has moved from the periphery to the very center of the technology boom. But which industry is best positioned - with the huge data sets and resources - to take advantage of machine learning? According to research by PwC, this industry is finance.
This workshop is free, where you will learn how to utilize keras to make a predicition of the number of customers based on historical data with only the requirements of:
Bringing your laptop
You need beginner level python knowledge
The Bootcamp Program
Our instructors have background in education, machine learning, but also educational technology research. Meaning we combine the best of all fields to provide you a learning experience far superior to anything in the market.
Companies using Tensorflow include Uber, Amazon, Salesforce, Netflix and many more. Salesforce recently spent 1.2 Billion dollars in 2018 on R&D on machine learning creating automation throughout their sales systems that would rank customers in order to prioritize, automate customer services through chatbots, and provide deep analysis of customers based on their phone number, email, company, job title, location and more.
We will cover:
Part 1 - Data Preprocessing and exploration
Part 2 - Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression, Random Forest Regression
Part 3 - Classification: Logistic Regression, Recurrent Neural networks
Part 4 - Introduction to LSTM
Part 5 - Univariate modelling with LSTM using Keras
Part 6 - Multivariate modelling with LSTM
Part 7 - Finetuning parameters using Tensorbard
Part 8 - Stacked LSTM modeling
As well, since 60% of the time is spent on debugging our algorithms, we will cover a visual library, Tensorboard, that lets us interact and change our algorithm visually and in real time in order to much more efficiently debug and draw interpretability for our algorithms.
Join us and master applied data science for finance today.
Our program is intensive, thorough, intuitive, visual, and project based. Avoid spending years in academy to master the same concepts when you can learn them in an accelerated program instead. Your time is precious to us. When we say we will provide you with the knowledge required for the industry, we ensure that this is true our you will get your money back 100% guaranteed.
"I think the Diggit Academy system for learning React is very good. It's a new way to learn new skills, and I liked it. The system allows the user to get automatic feedback on their precise mistake. I am very satisfied that I can learn new technology so quickly." ~ Jon Magnus Stavik Vold ( ICT Consultant at Ciber Norge AS)
Please contact us at [masked]