1. Why Python?
1. Classical definition and Prologue.
2. History (Initial development and “light hill report”)
3. Why python ? (My Formidable Questions)
4. Scripting language and its private heap.
5. Inside python
6. Interpreter of python.
7. Machine Learning in a nutshell
8. Tuning Hyperparameters
9. Hyperparameters
10. Final Conclusion
2. Classical definition and Prologue
• Definition: Science of getting computer to act without explicitly
programmed.
• My temperament is to comprehend the core – the intellect part. E.g.:
React.js
• Only Encapsulated methods: test and train method – only deliberate
practice is needed – strong whim arose.
3. History (Initial development and “light hill
report”)
• Can machines able to think ? And Checkers program.
• Light-hill report.
• Geoffrey Hinton gave impetus.
• Python language provides
4. Why python ? (My Formidable Questions)
• Usual reasons to why it was implemented in python.
1. Large corporates (google, tesla) have invested.
2. Built-in libraries availability.
3. Easy to use.
• Counter Questions
5. Scripting language and Private heap
• Python: Scripting language
• React native vs flutter
• Private heap.
6. Inside python
• Compiler in python..!
• Byte-code and Python Virtual machine: Given in Figure 1.1.
• My questions: Not separate file generated – how only interpreted.
10. Hyperparameters
• ROC: An ROC curve (receiver operating characteristic curve) is a graph
showing the performance of a classification model at all classification
thresholds.
• Confusion matrix: Confusion matrix, also known as an error matrix, is
a specific table layout that allows visualization of the performance of
an algorithm.
