Python është një gjuhë shumë e njohur programimi e cila përdoret në një server për ndërtimin e aplikacioneve Web dhe jo vetëm. Ky trajnim është ndërtuar për të ju tërhequr pas botës së programimit në gjuhën Python, kështu që është programi i duhur si për fillestarët, ashtu edhe për ata që kanë njohuri në programim.
1.1 Introduction
1.2 Hardware and Software
1.3 Data Hierarchy
1.4 Machine Languages, Assembly Languages and High-Level Languages
1.5 Introduction to Object Technology
1.6 Operating Systems
1.7 Python 1.8 It’s the Libraries! 1.9 Other Popular Programming Languages 1.10 Test-Drive: Using IPython and Jupyter Notebooks 1.11 Internet and World Wide Web 1.12 Software Technologies 1.13 How Big Is Big Data? 1.14 Case Study—A Big-Data Mobile Application 1.15 Intro to Data Science: Artificial Intelligence—at the Intersection of CS and Data Science Exercises2.1 Introduction
2.2 Variables and Assignment Statements
2.3 Arithmetic
2.4 Function print and an Intro to Single- and Double-Quoted Strings
2.5 Triple-Quoted Strings
2.6 Getting Input from the User 2.7 Decision Making: The if Statement and Comparison Operators 2.8 Objects and Dynamic Typing 2.9 Intro to Data Science: Basic Descriptive Statistics 2.10 Wrap-Up Exercises3.1 Introduction
3.2 Algorithms
3.3 Pseudocode
3.4 Control Statements
3.5 if Statement
3.6 if;…else and if;…elif;…else Statements 3.7 while Statement 3.8 for Statement 3.9 Augmented Assignments 3.10 Program Development: Sequence-Controlled Repetition 3.11 Program Development: Nested Control Statements 3.12 Built-In Function range: A Deeper Look 3.13 Using Type Decimal for Monetary Amounts 3.14 break and continue Statements 3.15 Boolean Operators And, Or and Not 3.16 Intro to Data Science: Measures of Central Tendency—Mean, Median and Mode 3.17 Wrap-Up Exercises4.1 Introduction
4.2 Defining Functions
4.3 Functions with Multiple Parameters
4.4 Random-Number Generation
4.5 Case Study: A Game of Chance
4.6 Python Standard Library 4.7 math Module Functions 4.8 Using IPython Tab Completion for Discovery 4.9 Default Parameter Values 4.10 Keyword Arguments 4.11 Arbitrary Argument Lists 4.12 Methods: Functions That Belong to Objects 4.13 Scope Rules 4.14 import: A Deeper Look 4.15 Passing Arguments to Functions: A Deeper Look 4.16 Function-Call Stack 4.17 Functional-Style Programming 4.18 Intro to Data Science: Measures of Dispersion 4.19 Wrap-Up Exercises5.1 Introduction
5.2 Lists
5.3 Tuples
5.4 Unpacking Sequences
5.5 Sequence Slicing
5.6 del Statement 5.7 Passing Lists to Functions 5.8 Sorting Lists 5.9 Searching Sequences 5.10 Other List Methods 5.11 Simulating Stacks with Lists 5.12 List Comprehensions 5.13 Generator Expressions 5.14 Filter, Map and Reduce 5.15 Other Sequence Processing Functions 5.16 Two-Dimensional Lists 5.17 Intro to Data Science: Simulation and Static Visualizations 5.18 Wrap-Up Exercises6.1 Introduction
6.2 Dictionaries
6.3 Sets
6.4 Intro to Data Science: Dynamic Visualizations
6.5 Wrap-Up
Exercises7.1 Introduction
7.2 Creating arrays from Existing Data
7.3 array Attributes
7.4 Filling arrays with Specific Values
7.5 Creating arrays from Ranges
7.6 List vs. array Performance: Introducing timeit
7.7 array Operators
7.8 NumPy Calculation Methods
7.9 Universal Functions
7.10 Indexing and Slicing
7.11 Views: Shallow Copies
7.12 Deep Copies
7.13 Reshaping and Transposing
7.14 Intro to Data Science: pandas Series and DataFrames
7.15 Wrap-Up
Exercises8.1 Introduction
8.2 Formatting Strings
8.3 Concatenating and Repeating Strings
8.4 Stripping Whitespace from Strings
8.5 Changing Character Case
8.6 Comparison Operators for Strings
8.7 Searching for Substrings
8.8 Replacing Substrings
8.9 Splitting and Joining Strings
8.10 Characters and Character-Testing Methods
8.11 Raw Strings
8.12 Introduction to Regular Expressions
8.13 Intro to Data Science: Pandas, Regular Expressions and Data Munging
8.14 Wrap-Up
Exercises9.1 Introduction
9.2 Files
9.3 Text-File Processing
9.4 Updating Text Files
9.5 Serialization with JSON
9.6 Focus on Security: pickle Serialization and Deserialization
9.7 Additional Notes Regarding Files
9.8 Handling Exceptions
9.9 finally Clause
9.10 Explicitly Raising an Exception
9.11 (Optional) Stack Unwinding and Tracebacks
9.12 Intro to Data Science: Working with CSV Files
9.13 Wrap-Up
Exercises10.1 Introduction
10.2 Custom Class Account
10.3 Controlling Access to Attributes
10.4 Properties for Data Access
10.5 Simulating “Private” Attributes
10.6 Case Study: Card Shuffling and Dealing Simulation
10.7 Inheritance: Base Classes and Subclasses
10.8 Building an Inheritance Hierarchy; Introducing Polymorphism
10.9 Duck Typing and Polymorphism
10.10 Operator Overloading
10.11 Exception Class Hierarchy and Custom Exceptions
10.12 Named Tuples
10.13 A Brief Intro to Python 3.7’s New Data Classes
10.14 Unit Testing with Docstrings and doctest
10.15 Namespaces and Scopes
10.16 Intro to Data Science: Time Series and Simple Linear Regression
10.17 Wrap-Up
Exercises11.1 Introduction
11.2 Factorials
11.3 Recursive Factorial Example
11.4 Recursive Fibonacci Series Example
11.5 Recursion vs. Iteration
11.6 Self Check
11.6 Searching and Sorting
11.7 Linear Search
11.8 Efficiency of Algorithms: Big O
11.9 Binary Search
11.10 Sorting Algorithms
11.11 Selection Sort
11.12 Insertion Sort
11.13 Merge Sort
11.14 Big O Summary for This Chapter’s Searching and Sorting Algorithms
11.15 Visualizing Algorithms
11.16 Wrap-Up
Exercises12.1 Introduction
12.2 TextBlob1
12.3 Visualizing Word Frequencies with Bar Charts and Word Clouds
12.4 Readability Assessment with Textatistic
12.5 Named Entity Recognition with spaCy
12.6 Similarity Detection with spaCy
12.7 Other NLP Libraries and Tools
12.8 Machine Learning and Deep Learning Natural Language Applications
12.9 Natural Language Datasets
12.10 Wrap-Up
Exercises13.1 Introduction
13.2 Overview of the Twitter APIs
13.3 Creating a Twitter Account
13.4 Creating an AppGetting Twitter Credentials—Creating an App
13.5 What’s in a Tweet?
13.6 Tweepy
13.7 Authenticating with Twitter Via Tweepy
13.8 Getting Information About a Twitter Account
13.9 Introduction to Tweepy Cursors: Getting an Account’s Followers and Friends
13.10 Searching Recent Tweets
13.11 Spotting Trends: Twitter Trends API
13.12 Cleaning/Preprocessing Tweets for Analysis
13.13 Twitter Streaming API
13.14 Tweet Sentiment Analysis
13.15 Geocoding and Mapping
13.16 Ways to Store Tweets
13.17 Twitter and Time Series
13.18 Wrap-Up
Exercises14.1 Introduction: IBM Watson and Cognitive Computing
14.2 IBM Cloud Account and Cloud Console
14.3 Watson Services
14.4 Additional Services and Tools
14.5 Watson Developer Cloud Python SDK
14.6 Case Study: Traveler’s Companion Translation App
14.7 Watson Resources
14.8 Wrap-Up
Exercises15.1 Introduction to Machine Learning
15.2 Case Study: Classification with k-Nearest Neighbors and the Digits Dataset, Part 1
15.3 Case Study: Classification with k-Nearest Neighbors and the Digits Dataset, Part 2
15.4 Case Study: Time Series and Simple Linear Regression
15.5 Case Study: Multiple Linear Regression with the California Housing Dataset
15.6 Case Study: Unsupervised Machine Learning, Part 1—Dimensionality Reduction
15.7 Case Study: Unsupervised Machine Learning, Part 2—k-Means Clustering
15.8 Wrap-Up
Exercises16.1 Introduction
16.2 Keras Built-In Datasets
16.3 Custom Anaconda Environments
16.4 Neural Networks
16.5 Tensors
16.6 Convolutional Neural Networks for Vision; Multi-Classification with the MNIST Dataset
16.7 Visualizing Neural Network Training with TensorBoard
16.8 ConvnetJS: Browser-Based Deep-Learning Training and Visualization
16.9 Recurrent Neural Networks for Sequences; Sentiment Analysis with the IMDb Dataset
16.10 Tuning Deep Learning Models
16.11 Convnet Models Pretrained on ImageNet
16.12 Reinforcement Learning
16.13 Wrap-Up Exercises17.1 Introduction
17.2 Relational Databases and Structured Query Language (SQL)
17.3 NoSQL and NewSQL Big-Data Databases: A Brief Tour
17.4 Case Study: A MongoDB JSON Document Database
17.5 Hadoop
17.6 Spark
17.7 Spark Streaming: Counting Twitter Hashtags Using the pyspark-notebook Docker Stack
17.8 Internet of Things and Dashboards
17.9 Wrap-Up
Exercises