About Us

Based in Toronto, Canada, we're a group of machine learning engineers, quantitative analysts, and quantum computing enthusiasts.

MLQ Articles

The articles on MLQ are broadly categorized into Machine Learning, Quantum Computing, and Quantitative Finance. Below are a few top articles from each category.

Machine Learning

• What is Machine Learning? A Complete Guide for Beginners
• The Ultimate Guide to Artificial Intelligence for Business
• What is TensorFlow & How Are Businesses Using It?
• What is Edge AI? Value Propositions & Industry Use Cases
• AI in Advertising: Real-Time Bidding & Reinforcement Learning
• Tensor Processing Units (TPUs) for Accelerated Machine Learning
• AI for Ecommerce: Optimizing Business Processes with Reinforcement Learning
• AI for Ecommerce: Maximizing Revenues with Thompson Sampling
• Directing App Users to Paid Subscriptions with Machine Learning
• An Introduction to Deep Learning with PyTorch
• Introduction to Transfer Learning with TensorFlow 2.0
• An Introduction to DeepDream with TensorFlow 2.0
• Introduction to Recommendation Systems with TensorFlow
• How to Build Production-Level Machine Learning Systems

Unsupervised Learning

• Unsupervised Learning Stock Market Clustering with K-Means

Recurrent Neural Networks & LSTMs

• A Complete Guide to Recurrent Neural Networks & LSTMs
• Recurrent Neural Networks (RNNs) and LSTMs for Time Series Forecasting

Convolutional Neural Networks

• How to Build a Convolutional Neural Network in Python with Keras
• What are Convolutional Neural Networks? A Complete Guide to CNNs
• Introduction to Convolutional Neural Networks (CNNs) with TensorFlow

Generative Models

• Generative Modeling: What is a Variational Autoencoder
• What are Generative Adversarial Networks (GANs)
• Synthetic Financial Data with Generative Adversarial Networks (GANs)
• Introduction to Generative Adversarial Networks (GANs): Intuition & Theory
• Introduction to Deep Convolutional GANs (DCGANs)
• Introduction to Wasserstein GANs with Gradient Penalty
• Introduction to Conditional GANs (cGANs) & Controllable Generation

Reinforcement Learning

• What is Reinforcement Learning? A Complete Guide for Beginners
• The Ultimate Guide to Deep Reinforcement Learning
• An Overview of Deep Reinforcement Learning for Trading
• Deep Reinforcement Learning: Guide to Deep Q-Learning
• Deep Reinforcement Learning: Twin Delayed DDPG Algorithm
• Deep Reinforcement Learning for Trading with TensorFlow 2.0
• Implementing Deep Reinforcement Learning with PyTorch: Deep Q-Learning
• Deep Reinforcement Learning for Trading: Strategy Development & AutoML
• Fundamentals of Reinforcement Learning: Estimating the Action-Value Function
• Fundamentals of Reinforcement Learning: Policies, Value Functions & the Bellman Equation
• Fundamentals of Reinforcement Learning: Markov Decision Processes
• Fundamentals of Reinforcement Learning: Dynamic Programming
  

Natural Language Processing

• Introduction to Natural Language Processing (NLP) with Python
• Introduction to Deep Learning for Natural Language Processing
• Introduction to Natural Language Processing (NLP) with TensorFlow
• Naive Bayes for Sentiment Analysis & Natural Language Processing (NLP)
• Natural Language Processing (NLP) for Sentiment Analysis with Logistic Regression

Mathematics of Machine Learning

• Mathematics of Machine Learning: Introduction to Linear Algebra
• Mathematics of Machine Learning: Introduction to Multivariate Calculus
• Mathematics of Machine Learning: Introduction to Probability Theory

Model Deployment

• Introduction to Deploying Machine Learning Models with Django

Data Engineering

• Introduction to Data Engineering, Data Lakes, and Data Warehouses
• Data Lakes vs. Data Warehouses: Key Concepts & Use Cases with GCP

SQL for Data Science

• SQL for Data Science: Selecting and Retrieving Data
• SQL for Data Science: Filtering, Sorting, and Calculating Data
• SQL for Data Science: Subqueries and Joins
  

Other

• Introduction to Genetic Algorithms: Intuition & Python Implementation

Quantum Computing

• What is Quantum Computing? Key Concepts & Industry Use Cases
• Quantum Machine Learning: Introduction to Quantum Systems
• Quantum Machine Learning: Introduction to Quantum Computation
• Quantum Machine Learning: Introduction to Quantum Learning Algorithms
• Introduction to Quantum Programming with Google Cirq
• Quantum Programming with the D-Wave Quantum Annealer
• Introduction to Quantum Programming with Qiskit
• Advanced Mathematics of Quantum Computing
• Quantum Machine Learning: Introduction to TensorFlow Quantum

Quantitative Finance

• Machine Learning for Finance: Price Prediction with Linear Regression
• Classification-Based Machine Learning for Finance
• Introduction to Python for Finance and Algorithmic Trading
• Python for Finance: Data Visualization
• Python for Finance: Time Series Analysis
• Python for Finance: Portfolio Optimization
• Introduction to Algorithmic Trading with Quantopian
• Introduction to the Capital Asset Pricing Model (CAPM) with Python
• Introduction to Quantitative Modeling: Linear Models
• Introduction to Quantitive Modeling: Probabilistic Models
• Introduction to Quantitative Modeling: Regression Models
• Introduction to Portfolio Construction and Analysis: Risk & Returns
• Introduction to Markowitz Portfolio Optimization and the Efficient Frontier
• What is Quantamental Investing?
• Applications of AI and Machine Learning in Venture Capital

Contact Us

You can contact us with any queries relating to MLQ at support@mlq.ai.