Training a Neural Network - Implementing Backpropagation and Gradient Descent from Scratch
Implement backpropagation and gradient descent from scratch in Python, training a neural network to perform arithmetic sum. Includes step-by-step coding and explanations.
Automated Insights in Finance Using Machine Learning & AI
Explore AI and ML techniques for extracting actionable insights from alternative data sources in finance, leading to profitable trading strategies and robust portfolio construction.
How AI Is Changing the Shopping Experience
Explore how AI revolutionizes retail, enhancing customer experiences and streamlining operations. Learn about personalized shopping, data quality, and future trends in e-commerce.
Deep Learning Survival Analysis for Consumer Credit Risk Modelling
Explore deep learning survival analysis for precise credit risk prediction in consumer lending, combining traditional methods with advanced techniques for improved time-to-event forecasting.
Humans & AI in Financial Services - The Future - Samik Chandarana - ODSC Europe 2019
Explore the future of AI in finance with Samik Chandarana's keynote, covering data-driven decisions, deep neural nets, and AI applications in trading, payments, and natural language processing.
Price Optimisation - From Exploration to Productionising - David Adey, PhD & Alexey Drozdetskiy, PhD
Explore dynamic price optimization using machine learning, from data analysis to cloud deployment. Learn about feature encoding, model selection, efficiency improvements, and practical implementation strategies for revenue growth.
Counterfactual Evaluation of Machine Learning Models
Explore counterfactual evaluation techniques for machine learning models, focusing on charge outcomes and iterative improvements in financial technology applications.
Fraud Detection in Bitcoin Payment Networks
Explore fraud detection in Bitcoin networks using machine learning, covering techniques like deep learning and entity recognition for effective cryptocurrency security.
Applied Machine Learning for Startups - Arshak Navruzyan
Applied ML strategies for startups: practitioner training, team structures, guidelines, and cutting-edge techniques in NLP and deep learning.
Luis von Ahn: Pioneering Crowdsourcing and Language Learning with Duolingo
Pioneering crowdsourcing: From reCAPTCHA to Duolingo. Insights on harnessing collective intelligence for free language learning, tech entrepreneurship, and the impact of accessible education.
The Four Pegs of Requirements Engineering with Bertrand Meyer
Explore the four pillars of requirements engineering with Bertrand Meyer, covering concepts, definitions, and practical guidelines to improve software project outcomes.
Tradeoffs in the Software Workflow
Explore tradeoffs in software workflows, balancing fast releases with best practices. Learn strategies for reducing work-in-progress, optimizing value delivery, and managing technical debt in modern software engineering.
Challenges and Opportunities in Responsible AI
Explore challenges and opportunities in responsible AI development, focusing on human-centered approaches, cultural shifts, and tooling advances to address risks and ensure societal benefits.
Addressing Issues of Equity and Youth Agency in Computing Education Through a Graphic Novel
Explore equity and youth agency in computing education through a graphic novel, empowering students and educators to critically engage with technology's ethical complexities and societal impact.
Maximizing the Potential of Documents, NLP, and AI - Technical and Non-technical Challenges
Explore technical and non-technical challenges in maximizing document potential with NLP and AI, focusing on SEEK's employment marketplace and innovative solutions for data processing and team organization.
The Essence of Software - Why Systems Often Fail by Design, and How to Fix Them
Explore software design flaws, their impact on user experience, and innovative solutions using concept-based approaches. Learn to create more intuitive and effective systems.
Optimization Crash Course
Explore geometric methods in optimization and sampling, covering key topics like convexity, optimality, and gradient descent with expert insights from MIT's Ashia Wilson.
Deep Robust Reinforcement Learning and Regularization
Explore robust reinforcement learning, addressing uncertainties in deep RL through regularization techniques. Gain insights into robust MDPs, policy evaluation, and uncertainty-aware Bellman equations.
The AI Economist- Improving Equality and Productivity with AI-Driven Tax Policies
Explore AI-driven tax policies for improved economic equality and productivity, featuring deep learning, reinforcement learning, and multi-agent simulations in a simplified economic model.
Machine Learning-Based Design of Proteins
Explore machine learning-based protein design with Jennifer Listgarten, covering directed evolution, predictive models, and optimization techniques for gene therapy applications.
Zexe- Enabling Decentralized Private Computation
Explore decentralized private computation with ZEXE, addressing scalability and privacy in blockchain systems for digital asset trading and custom access control.