PickAClass · Trading, Investing & Money · Algorithmic & Quantitative Trading

Machine Learning for Trading

Apply machine learning models, including regression, classification, and reinforcement learning, to predict market movements and generate trading signals.

Machine Learning for Trading

XGBoost Regression: Build and Tune Predictive Machine Learning Models

Feature Engineering with TensorFlow: Processing Numeric Inputs for ML

Programming vs Machine Learning: A Beginner's Guide to the Paradigm Shift

Building a Simple Linear Classifier in Python

Machine Learning Project Lifecycle: From Data to Deployment

Mapping the Loss Surface: Gradient Descent Fundamentals in NumPy

Foundations of Multiple Regression and Gradient Descent

One-Hot Encoding with TensorFlow for Machine Learning

Understanding Perceptrons and Their Limits in Machine Learning

Sigmoid Activation and Binary Classification with NumPy

TensorFlow Estimators for Structured Data and Model Execution

Calculating Perceptron Model Error Across Multiple Data Points

Foundations of TensorFlow for Machine Learning in Python

Machine Learning with Weka: Practical Data Mining and Analysis

Automated Feature Engineering with FeatureTools and pandas

Predictive Modeling with PyCaret: From Training to Evaluation

Tuning the Learning Rate in Linear Regression

Gradient Descent and Optimization for Predictive Models in Python

Regression Modeling with PyCaret: Low-Code Machine Learning

Gradient Boosting Regressors in Python: Rental Price Prediction

Dataset Splitting Strategies for Machine Learning in Python

Election Forecasting with Python: Random Variables and Sampling

Evaluating Machine Learning Models with TensorFlow Estimators

Machine Learning with PyCaret: Setting Up Regression Workflows