Martin Pring – 2 Day Personal Training Course (Seminar Package)
Nonparametric Econometrics - Theory and Practice
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Macroeconomic Forecasting In The Era Of Big Data - Theory And Practice
Suresh Sundaresan – Continuous-Time Methods in Finance. A Review and an Assessment
FX Traders Classroom – Introduction To Forex Trading
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Description
The tools and techniques that you need to get really good at applied machine learning, really fast.
Here is everything you get in this 28-book set:
- Machine Learning Mastery With R
- Deep Learning With Python
- XGBoost With Python
- Master Machine Learning Algorithms
- ML Algorithms From Scratch
- Machine Learning Mastery With Weka
- Machine Learning Mastery With Python
- Time Series Forecasting With Python
- LSTM Networks With Python
- Deep Learning for NLP
- Linear Algebra for Machine Learning
- Statistical Methods for Machine Learning
- Deep Learning for Time Series
- Better Deep Learning
- Deep Learning for Computer Vision
- GANs with Python
- Probability for Machine Learning
- Imbalanced Classification with Python
- Data Preparation for Machine Learning
- Ensemble Learning Algorithms
- Optimization for Machine Learning
- Calculus for Machine Learning
- Python for Machine Learning
- Building Transformer Models with Attention
- Deep Learning with PyTorch
- Maximizing Productivity with ChatGPT
- Machine Learning in OpenCV
- The Beginner’s Guide to Data Science
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