🧩 Part 1/12

✔ What is Financial Machine Learning?
✔ How Financial Machine Learning Works
✔ Data Sources and Preprocessing
✔ Algorithms and Models
✔ Evaluation and Deployment
✔ Applications of Financial Machine Learning
✔ Algorithmic Trading
✔ Credit Scoring and Fraud Detection
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🧩 Part 2/12

✔ Data Sources for Financial Machine Learning
✔ Public Data Sources
✔ Private Data Sources
✔ Alternative Data Sources
✔ Data Preprocessing for Financial Machine Learning
✔ Data Cleaning and Validation
✔ Data Transformation and Normalization
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🧩 Part 3/12

✔ Supervised Learning Basics
✔ Regression
✔ Classification
✔ Supervised Learning Applications in Finance
✔ Stock Price Prediction
✔ Credit Risk Assessment
✔ Fraud Detection
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🧩 Part 4/12

✔ What is Unsupervised Learning?
✔ Why Use Unsupervised Learning for Financial Data?
✔ Types of Unsupervised Learning Methods
✔ Clustering
✔ Dimensionality Reduction
✔ Outlier Detection
✔ How to Apply Unsupervised Learning Methods to Financial Data?
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🧩 Part 5/12

✔ Reinforcement Learning Basics
✔ Agents, Environments, and Rewards
✔ Policy and Value Functions
✔ Exploration and Exploitation
✔ Reinforcement Learning Methods for Financial Problems
✔ Portfolio Optimization
✔ Trading Strategies
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🧩 Part 6/12

✔ Neural Networks for Financial Data
✔ Feedforward Networks
✔ Autoencoders
✔ Convolutional Networks for Financial Images
✔ Image Representation of Financial Data
✔ Convolutional Layers and Filters
✔ Recurrent Networks for Financial Time Series
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🧩 Part 7/12

✔ Natural Language Processing for Text Analysis
✔ Tokenization and Vectorization
✔ Topic Modeling and Clustering
✔ Named Entity Recognition and Relation Extraction
✔ Natural Language Processing for Text Generation
✔ Language Models and Transformers
✔ Text Summarization and Paraphrasing
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🧩 Part 8/12

✔ Computer Vision Basics
✔ Image Processing and Analysis
✔ Image Recognition and Classification
✔ Object Detection and Localization
✔ Face Recognition and Verification
✔ Financial Applications of Computer Vision
✔ Document Analysis and Extraction
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🧩 Part 9/12

✔ What is Time Series Analysis?
✔ Why is Time Series Analysis Important for Financial Machine Learning?
✔ Types of Time Series Data
✔ Stationarity and Non-Stationarity
✔ Autocorrelation and Partial Autocorrelation
✔ ARIMA Models
✔ LSTM Models
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🧩 Part 10/12

✔ Portfolio Optimization: Concepts and Methods
✔ What is Portfolio Optimization?
✔ How to Measure Portfolio Performance?
✔ What are the Common Portfolio Optimization Models?
✔ Portfolio Optimization for Financial Machine Learning
✔ How to Apply Machine Learning to Portfolio Optimization?
✔ What are the Benefits and Challenges of Machine Learning for Portfolio Optimization?
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🧩 Part 11/12

✔ What is Algorithmic Trading?
✔ Definition and Benefits
✔ Challenges and Risks
✔ How to Design Trading Strategies?
✔ Data Sources and Preprocessing
✔ Feature Engineering and Selection
✔ Trading Signal Generation and Optimization
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🧩 Part 12/12

✔ Ethical Challenges of Financial Machine Learning
✔ Privacy and Data Protection
✔ Security and Robustness
✔ Fairness and Bias
✔ Accountability and Transparency
✔ Regulatory Frameworks for Financial Machine Learning
✔ Global and Regional Initiatives
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