Amazing products without engaged clients are bound to fail, and companies claiming to have found the single best solution to client engagement are only fooling themselves. What seems to work today to keep your clients engaged won't necessarily work tomorrow. The "optimal" client engagement tactic for your product will change over time and companies must be fluid and … [Read more...] about How Stitch Fix Optimizes Client Engagement With Contextual Bandits
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3 Ways to Automate Marketing with Machine Learning
With the latest advances in technology, you can tap into a massive audience using all sorts of online and offline channels. However, these aren’t necessarily advantages. Without the right tools, it’s nearly impossible to figure out how and where to focus your marketing efforts. Automation makes marketing a lot less complex and exhausting. Implementing machine learning … [Read more...] about 3 Ways to Automate Marketing with Machine Learning
Multi-Touch Marketing Attribution Models: A Comprehensive Guide
We continue our comprehensive guide on historical marketing attribution models. In this article, we discuss multi-touch attribution approaches. Read about single-touch marketing attribution approaches in the first part of this series. Multi-Touch Marketing Attribution Models In contrast to single-touch models that assign a contributing value to just one touchpoint, the … [Read more...] about Multi-Touch Marketing Attribution Models: A Comprehensive Guide
Single-Touch Marketing Attribution Models: A Comprehensive Guide
In today’s expansive and dynamic digital economy, customers usually follow a complicated and multilayered approach before they finally convert into a sale or lead. For a prospect to become a customer, they usually make interactions with a wide range of digital touchpoints - paid advertisements, social media posts, email messages, and many other channels. This multitouch … [Read more...] about Single-Touch Marketing Attribution Models: A Comprehensive Guide
Top 8 Trends From ICLR 2019
1. Inclusivity The organizers pressed the importance of inclusivity in AI by making sure that the first two main talks, the Sasha Rush’s opening remarks and Cynthia Dwork’s invited talk, were about fairness and equality. Some of the worrisome statistics include: Only 8.6% of presenters and 15% of participants are women.2/3rd of all the LGBTQ+ researchers aren’t out … [Read more...] about Top 8 Trends From ICLR 2019
Intuitively Understanding Convolutions for Deep Learning
The advent of powerful and versatile deep learning frameworks in recent years has made it possible to implement convolution layers into a deep learning model an extremely simple task, often achievable in a single line of code. However, understanding convolutions, especially for the first time can often feel a bit unnerving, with terms like kernels, filters, channels and so … [Read more...] about Intuitively Understanding Convolutions for Deep Learning
Reinforcement Learning Explained: Overview, Comparisons and Applications in Business
Imagine you’re completing a mission in a computer game. Maybe you’re going through a military depot to find a secret weapon. You get points for the right actions (killing an enemy) and lose them for the wrong ones (falling into a pit or getting hit). If you’re playing on high difficulty, you might not conclude this task in just one attempt. Try after try, you learn which … [Read more...] about Reinforcement Learning Explained: Overview, Comparisons and Applications in Business
Reinforcement Learning From Scratch
Recently, I gave a talk at the O’Reilly AI conference in Beijing about some of the interesting lessons we’ve learned in the world of NLP. While there, I was lucky enough to attend a tutorial on Deep Reinforcement Learning (Deep RL) from scratch by Unity Technologies. I thought that the session, led by Arthur Juliani, was extremely informative and wanted to share … [Read more...] about Reinforcement Learning From Scratch
Intuitively Understanding Variational Autoencoders
In contrast to the more standard uses of neural networks as regressors or classifiers, Variational Autoencoders (VAEs) are powerful generative models, now having applications as diverse as from generating fake human faces, to producing purely synthetic music. This post will explore what a VAE is, the intuition behind why it works so well, and its uses as a powerful … [Read more...] about Intuitively Understanding Variational Autoencoders
Mixture of Variational Autoencoders – a Fusion Between MoE and VAE
The Variational Autoencoder (VAE) is a paragon for neural networks that try to learn the shape of the input space. Once trained, the model can be used to generate new samples from the input space. If we have labels for our input data, it’s also possible to condition the generation process on the label. In the MNIST case, it means we can specify … [Read more...] about Mixture of Variational Autoencoders – a Fusion Between MoE and VAE