دورة البايثون 4 | Repeating Events & Python Modules (NumPy, math, pandas) смотреть онлайн

Topics detailed
●Lecture 1: Getting Started with Python Introduction
○Introduction
○Installing Python & PyCharm
○Setup & Displaying Text
○Modules & Pip & Virtual environment
○Resources
●Lecture 2: Variables & Data Types in python
○Strings
○Numbers
○Dates and Times
○Python Operators
○Getting Input from Users
○Comments
●Lecture 3: Making Decisions & Complex Decisions in python
○If Statements & Comparisons
○Loop
○Building a Basic Calculator
○Errors and Exceptions: Try / Except
●Lecture 4: Repeating Events & Python Modules (NumPy, math, pandas)
○Repeating Events Until Done
○Lists
○Dataframe
●Lecture 5: Dictionaries & 2D Lists & Nested Loops in Python
○Building a Translator
●Lecture 6: File Handling & Functions in python
○How to Save Information in Files
○Reading from Files
○Functions
●Lecture 7: Handling Errors & Python Matplotlib
●Lecture 8: Machine learning: Supervised and Unsupervised learning I
○Types of machine learning
○Machine learning challenges
○How to prepare dataset
○How to optimize machine learning hyperparameter
●Lecture 9: Machine learning: Supervised and Unsupervised learning II
○Practical example (implementing wifi localization paper)
○Measurements metrics
●Lecture 10: Deep Learning & Reinforcement learning using PyTorch and Tensorflow I
○Neural Networks
○Convolutional Neural Networks
○Recurrent Neural Networks
○Gated Recurrent Unit (GRU)
○Long Short-Term Memory (LSTM)
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●Lecture 11 Deep Learning & Reinforcement learning using PyTorch and Tensorflow II
○Deep Q-Network (DQN)