AI for Digital Marketing

Last November I was invited to give a course on Artificial Intelligence for Digital Marketing at EBS school in Geneva. EBS stands for European Business School that was created jointly with CREA, which is specialised in digital communications and digital marketing. EBS runs bachelor’s and master’s degrees in digital business, which are nowadays quite relevant. AI for digital business is also very much relevant, as marketeers all over the world are usually among the first to adopt new technologies and new gadgets.

So, how can one leverage artificial intelligence in digital marketing ? I assume that readers know already the theory of artificial intelligence and main approaches (state-based algorithms, machine learning, deep learning), so I will not talk about the ML training process, cost functions, gradient descent, kernels, neural networks and other techniques. I will start with explaining the difference among very similar expressions used around artificial intelligence, then I will describe high-value use cases, and in the end how to successfully implement all this, so that your project flies like a rocket. So, I will stay with high-level and business-relevant explanations.

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Think 2019

February 12 – 15 was the week for Think 2019, according to some analysis the most important tech event of the year. IBM assembled together all major individual exhibitions and this was the second edition of Think, now the main annual IBM conference. This time the event took place in San Francisco. I attended the event as one of the speakers on the subject of Watson Machine Learning and Watson Studio, and in my session I also had as guest Anyline, AI company from Austria.

The conference was successful and it was huge. Not only based on the number of participants (around 30’000), or sessions (more than 3’000), but also on the quality of discussions and topics. IBM events are not so much about announcements, but I will list and describe the most important ones in this post, along with highlights of the most recent and interesting technologies.  Continue reading “Think 2019”

Deep Learning and Watson Studio

It was fun to play with Watson Studio and create my own convolutional neural network. Watson Studio is complex but easy and graphically intuitive tool, and integrates well with Watson Machine Learning engine. I used standard MNIST data set (with images of hand-written digits), created three layers deep CNN, exported the algorithm in TensorFlow / Keras, trained the model both using GPUs on Watson and locally on my Jupyter Python Macbook environment and got nice results. To data scientists and AI developers : go and use it. And for all other enthusiasts, the best way to learn AI is to create it yourself 🙂 ! Continue reading “Deep Learning and Watson Studio”