Hey guys, in this episode I talk about applications of GANs, Generative Adversarial Networks, in the real world. I talk about many applications in photo and video editing, super resolution, video games, autonomous driving and much more!

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Linkedin: https://www.linkedin.com/company/life-with-ai

Code: https://github.com/filipelauar/projects/tree/main/GAN_applications

In this episode I talk about different applications of artificial intelligence in the real world using CNN networks. I talk about 3 main problems, classification, detection and segmentation, explain what's being done in each of these problematic and also the state of the art to solve them.

Website to find state of the art models: https://paperswithcode.com/sota/

Instagram: https://www.instagram.com/podcast.lifewithai/

Linkedin: https://www.linkedin.com/company/life-with-ai

Code: https://github.com/filipelauar/projects/tree/main/CNN_applications

In this episode I'm with my friend Gabriel Oliva to talk about the use o Artificial Intelligence in the financial market. We talk about many applications, such as satellite analysis, price prediction, assets allocation and many more. We also discuss the use of AI more as a tool than a final solution.

Instagram: https://www.instagram.com/podcast.lifewithai/

Linkedin: https://www.linkedin.com/company/life-with-ai

Gabriel's Linkedin: https://www.linkedin.com/in/gabriel-oliva-199359148/

In this episode I'm with my friend Kevin Kühl to talk about the first steps to get into the financial market. We talk about different types of investments like fixed incomes and variable incomes, the stocks, the REITS and also the ETFs. If you want to now more about the financial market and is thinking to get into it, this episode is for you!

https://www.instagram.com/podcast.lifewithai/

Linkedin: https://www.linkedin.com/company/life-with-ai

Kevin's Linkedin: https://www.linkedin.com/in/kevinfkuhl/

In this episode I have as a guest my friend Kevin Kühl, which worked with modeling complex systems in the ICMC lab from USP in partnership with a lab at the Imperial College London. In the episode we talk about how modeling complex systems can help us understand the behavior of the human brain, the isolation system against Covid19 and even the hands clapping in a birthday party. Instagram: 

https://www.instagram.com/podcast.lifewithai/ 

Linkedin: https://www.linkedin.com/company/life-with-ai 

Kevin's Linkedin: https://www.linkedin.com/in/kevinfkuhl/

In this episode I talk about the problems of dimensionality reduction and clustering. I explain the applications of each one of these problems and also the most famous methods for solving them, such as PCA, KPCA, ICA and NNMF for the dimensionality reduction and the Kmeans for the clustering problems. In the end I also explain the autoencoders, which are powerfull neural networks that can be used for both problems.

Instagram: https://www.instagram.com/podcast.lifewithai/

Linkedin: https://www.linkedin.com/company/life-with-ai

Code: https://github.com/filipelauar/projects/tree/main/dimensionality%20reduction%20and%20clustering

In this episode I explain a new class of problems that are able to be solved from the neural network CycleGAN. With this new network, we are able to transform an image into another, such as transform a horse into a zebra, a cat into a dog of even a normal picture into a famous painting made by Van Gogh or Monet!

Instagram: https://www.instagram.com/podcast.lifewithai/

Linkedin: https://www.linkedin.com/company/life-with-ai

Code: https://github.com/filipelauar/projects

In this episode I explain the solution I had to win a kaggle competition in my university (Telecom Paris). I explain the different solutions I had and what I did to improve the results. In the end I also talk about a possible solution that could win against my own using ensembles.

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Linkedin: https://www.linkedin.com/company/life-with-ai

GitHub with the solution: https://github.com/filipelauar/Kaggle/blob/main/cancer_detection_challange_notebook.ipynb

In this episode I give various examples about racist algorithms in different domains like face recognition, healthcare insurance, crime probability, hate speech and much more! I talk not only about racial problems, but also about gender and religion problems caused by artificial intelligence algorithms.