The evolution of video understanding has followed a similar trajectory to language and image understanding - with the rise of large pre-trained foundation models trained on a huge amount of data. Given the surge of multimodal research lately, video foundation models are becoming even more powerful to decipher the rich visual information embedded in videos. This talk will explore diverse use cases of video understanding and provide a glimpse of Twelve Labs offerings.

The evolution of video understanding has followed a similar trajectory to language and image understanding - with the rise of large pre-trained foundation models trained on a huge amount of data. Given the surge of multimodal research lately, video foundation models are becoming even more powerful to decipher the rich visual information embedded in videos. This talk will explore diverse use cases of video understanding and provide a glimpse of Twelve Labs offerings.

Dive deep into how machine learning is transforming the financial industry with 'Machine Learning for Finance'. This comprehensive guide explores cutting-edge concepts in machine learning while providing practical insights and Python code examples to help readers apply these techniques to real-world financial scenarios. Whether tackling fraud detection, financial forecasting, or sentiment analysis, this book equips you with the understanding and tools needed to excel. What this Book will help me do Understand and implement machine learning techniques for structured data, natural language, images, and text. Learn Python-based tools and libraries such as scikit-learn, Keras, and TensorFlow for financial data analysis. Apply machine learning for tasks like predicting financial trends, detecting fraud, and customer sentiment analysis. Explore advanced topics such as neural networks, generative adversarial networks (GANs), and reinforcement learning. Gain hands-on experience with machine learning debugging, products launch preparation, and addressing bias in data. Author(s) James Le None and Jannes Klaas are experts in machine learning applications in financial technology. Jannes has extensive experience training financial professionals on implementing machine learning strategies in their work and pairs this with a deep academic understanding of the topic. Their dedication to empowering readers to confidently integrate AI and machine learning into financial applications shines through in this user-focused, richly detailed book. Who is it for? This book is tailored for financial professionals, data scientists, and enthusiasts aiming to harness machine learning's potential in finance. Readers should have a foundational understanding of mathematics, statistics, and Python programming. If you work in financial services and are curious about applications ranging from fraud detection to trend forecasting, this resource is for you. It's designed for those looking to advance their skills and make impactful contributions in financial technology.