Want to accelerate your learning?
ATTEND ODSC EAST 2023 IN BOSTON
LIVE TRAINING: NOVEMBER 15TH
If you can write a model in sklearn, you can make the leap to Bayesian inference with PyMC3, a user-friendly intro to probabilistic programming (PP) in Python. PP just means building models where the building blocks are probability distributions! And we can use PP to do Bayesian inference easily. Bayesian inference allows us to solve problems that aren’t otherwise tractable with classical methods.
The intention is to get hands-on experience building PyMC3 models to demystify probabilistic programming / Bayesian inference for those more well versed in traditional ML, and, most importantly, to understand how these models can be relevant in our daily work as data scientists in business.
Let’s build up our knowledge of probabilistic programming and Bayesian inference! All you need to start is basic knowledge of linear regression; familiarity with running a model of any type in Python is helpful.
TOP RATED ON-DEMAND BOOTCAMP
AVAILABLE ON-DEMAND
This 6-weeks Bootcampis an introduction to deep neural networks that brings high-level theory to life with working, interactive examples featuring TensorFlow 2, Keras, and PyTorch — all three of the principal Python libraries for deep learning. Essential theory will be covered in a manner that provides students with a complete intuitive understanding of deep learning’s underlying foundations.
Paired with hands-on code demos in Jupyter notebooks as well as strategic advice for overcoming common pitfalls, this foundational knowledge will empower individuals with no previous understanding of artificial neural networks to build production-ready deep learning applications across all of the contemporary families
Certificates & Bootcamps
Live training student experience
Time Series Forecasting with Python
All clear and well explained by our very knowledgable instructor, Marta. This was all extremely applicable to my job. Wish this was a full day instead as Marta had a lot of amazing content. Thanks to the instructor and organizers.
Hands-On Intro to Unsupervised Learning
I had a bit of previous experience with some of the techniques and was looking for more in-depth. Got all I wanted. Ankur has a great presentation style and excellent examples. I particularly appreciated Ankur’s answers to my numerous questions. Those answers alone were worth the price because they provided insight into real-world applications of these models. I also liked the use of live demo in the TensorFlow projector to visualize the results of every algorithm. Will adopt it right away.
NLP Fundamentals in Python
Matt took us through difficult terrain with ease, making sure everybody was on the same page throughout. Really great teaching! Incredibly useful!
Advanced Fraud Modeling
Aric is a great teacher and the entire class was structured very well. I learned a lot of new interesting techniques. A mix of lecture and live coding with real-time incorporation of student feedback and questions into the class. Best for intermediate to advanced data folks because it assumes you know some Python. I would highly recommend if you have an interest to learn fraud.
Practical Advanced Pandas
I like the hands-on approach to teaching the additional techniques of Pandas, and I greatly appreciate the availability of the course’s code for me to review later.
