Udemy Python Tutorial & Máy học vạn năng cho Financial Analysis
₫ 385.600
Sản phẩm Udemy Python Tutorial & Máy học vạn năng cho Financial Analysis đang được mở bán với mức giá siêu tốt khi mua online, giao hàng online trên toàn quốc với chi phí tiết kiệm nhất,0 đã được bán ra kể từ lúc chào bán lần cuối cùng.Trên đây là số liệu về sản phẩm chúng tôi thống kê và gửi đến bạn, hi vọng với những gợi ý ở trên giúp bạn mua sắm tốt hơn tại Pricespy Việt Nam
Inclusive flash drive 16GB
100% Work.
100% active permanently
What you 'll learn
Master Python 3 programming fundamentals for Data Science and Machine Learning with focus on Finance.
Understand how to leverage the power of Python to apply key financial concepts such as calculating daily portfolio returns risk and Sharpe ratio.
Understand the theory and intuition behind Capital Asset Pricing Model (CAPM), Markowitz portfolio optimization, and efficient frontier.
Apply Python to implement several trading strategies such as momentum-based and moving average trading strategies.
Understand how to use Jupyter notes for developing, presenting and sharing Data Science projects.
Learn how to use key Python Libraries such as NumPy for scientific computing, Pandas for data Analysis, Matplotlib for data plotting / visualization, and Seaborn for statistical plot.
Master SciKit-Learn library to build, train and tune machine learning models using real-world datasets.
Apply machine and deep learning models to solve real-world problems in the banking and finance sectors such as stock prices predictions, security news sentiment analysis, credit card fraud detection, bank customer segmentation, and loan default prediction.
Understanding the theory and intuition behind several machine learning algorithms for regression tasks (simple / multiple / polynomial), classification and clustering (K-Me
100% Work.
100% active permanently
What you 'll learn
Master Python 3 programming fundamentals for Data Science and Machine Learning with focus on Finance.
Understand how to leverage the power of Python to apply key financial concepts such as calculating daily portfolio returns risk and Sharpe ratio.
Understand the theory and intuition behind Capital Asset Pricing Model (CAPM), Markowitz portfolio optimization, and efficient frontier.
Apply Python to implement several trading strategies such as momentum-based and moving average trading strategies.
Understand how to use Jupyter notes for developing, presenting and sharing Data Science projects.
Learn how to use key Python Libraries such as NumPy for scientific computing, Pandas for data Analysis, Matplotlib for data plotting / visualization, and Seaborn for statistical plot.
Master SciKit-Learn library to build, train and tune machine learning models using real-world datasets.
Apply machine and deep learning models to solve real-world problems in the banking and finance sectors such as stock prices predictions, security news sentiment analysis, credit card fraud detection, bank customer segmentation, and loan default prediction.
Understanding the theory and intuition behind several machine learning algorithms for regression tasks (simple / multiple / polynomial), classification and clustering (K-Me
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