In this video, you will learn how to use an external python function to run your data through a forecast evaluation. Using Python files uploaded to the cloud environment within the Azure Machine Learning Studio, you can call functions within those files from the Jupyter Notebooks within the same cloud environment.
Convolutional Neural Networks(CNN) Week 3 Lecture 5 : Bounding Box Predictions
**** Best Books on Machine Learning :
1. Introduction to Machine Learning with Python: A Guide for Data Scientists: https://amzn.to/2TLlhAR
2. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems: https://amzn.to/2wKtPij
3. Pattern Recognition and Machine Learning (Information Science and Statistics): https://amzn.to/33aNXpL
4. Deep Learning with Python – François Chollet: https://amzn.to/39ISNgv
5. Deep Learning (Adaptive Computation and Machine Learning series) – Ian Goodfellow: https://amzn.to/2vMPVR7
6. Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series) – Kevin P. Murphy: https://amzn.to/33aNrYN
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When you hear that 70% percent of trading volume in the entire US stock market is generated by algorithms, you might think you are missing out something big. Are we the only fools in the market who still trade the traditional way? Do us mere mortals even stand a chance against the mighty machines?