I Hate You, NLP
Explore sentiment analysis in Python, from basic semantic mapping to advanced machine learning techniques. Learn pitfalls, see hands-on code, and discover tools for accurate emotion detection in text data.
A Gentle Introduction to Neural Networks - with Python
Explore neural networks and create your own using Python. Learn about AI challenges, biologically-inspired networks, training methods, and achieve 97.5% accuracy in recognizing handwritten numbers.
An Introduction to Deep Learning
Comprehensive introduction to deep neural networks, covering theory, training methods, and applications in image processing, speech recognition, and text analysis.
A Gentle Introduction to Data Science
Explore data science fundamentals, from AI's influence to practical machine learning in Python. Covers key concepts, problem-solving applications, and essential Python tools for aspiring data scientists.
An Introduction to PyTorch & Autograd
Explore PyTorch's dynamic computation graphs and Autograd package for efficient deep learning, with practical examples and insights into GPU processing and algorithmic differentiation.
Deep Learning Your Broadband Network at Home
Automate internet speed tests, log data, and analyze time series using Python. Learn data mining, visualization, and anomaly detection techniques like ARIMA and LSTM for broadband network performance.
Introduction to TensorFlow
Aprende los conceptos básicos de deep learning y TensorFlow, desde la instalación hasta la creación de redes neuronales, a través de ejemplos prácticos y visualizaciones amigables.
Data Is Not Flat
Explore feature engineering techniques for low-dimensional data to enhance model performance, with a focus on neural network classification and practical examples.
When to Use Machine Learning - Tips, Tricks and Warnings
Discover when and how to effectively apply machine learning, with practical tips and real-world examples from open-source projects and cryptocurrency trading.
May the Fuzz Be with You
Explore how LSTM neural networks and Python can generate AI-driven test inputs for software testing and network security, improving upon traditional fuzzing techniques.
How to Train an Image Classifier Using PyTorch
Learn to build an image classifier using PyTorch in this hands-on tutorial. Covers data preparation, model selection, training techniques, and evaluation, with practical tips and code examples for immediate implementation.
Supercharge Your Deep Learning Algorithms with Optimized Software
Optimize deep learning algorithms on Intel architecture using Intel® MKL for training and Intel® nGraph and OpenVINO™ for inferencing, enhancing runtime performance.
Natural Language Processing with Neural Networks
Dive deep into NLP with neural networks, exploring architectures, feature engineering, and practical tips for optimal results while considering computational costs and interpretability.
Machine Learning for Everyone
Discover the essentials of machine learning, neural networks, and reinforcement learning in this engaging talk. Gain practical insights and witness a mind-blowing demo to kickstart your ML journey.
Why Transformers Work
Explore the inner workings of transformers in machine learning, their advantages over RNNs, and applications in NLP and dialogue handling, with live demos and clear explanations.
Is the News Media Polarized? Or Are We Being Conditioned to Think It Is?
Explore the intersection of computer science and media bias analysis, examining perceived polarization in news through neural networks and SVMs, with surprising insights on mainstream media's impact.
Understanding Neural Network Architectures with Attention and Diffusion
Explore Attention and Diffusion models in neural networks, focusing on their applications in language processing and image synthesis, with simplified diagrams for visual learners.
Data Analytics Explained for Business Leaders
Demystifying data analytics for business leaders, bridging the gap between technical and strategic understanding to drive innovation, productivity, and informed decision-making.
Building Stable Kernel Trees with Machine Learning
Explore machine learning techniques for building stable kernel trees, focusing on automated patch review and neural network applications in kernel development.
Everything a Swift Dev Needs to Know About Machine Learning
Discover how machine learning impacts Swift development, exploring techniques, tools, and resources. Learn to leverage iOS for data gathering and model implementation using native code.
Machine Learning in the Browser
Explore the frontier of machine learning in web browsers, covering state-of-the-art libraries, implementation challenges, and performance optimization techniques for browser-based ML applications.