Programming: 4 Books in 1: Python Programming & Crash Course, Machine Learning for Beginners, Python Machine Learning
Have you always wanted to jump into the exciting world of Python programming and Machine Learning but didn’t know where to start? If so, then this book collection was made just for you.
Python is one of the most used programming languages in the world right now. Whether you are interested in Machine Learning, app development, or game design you can do it all with this programming language if you understand the basics. Since Python itself is a general-purpose language there is no end to what you can do with it. The only real limiting factor once you learn the ins and outs of Python programming is your imagination!
This bundle will teach you step-by-step what you need to know to get started with Python and be familiar with Machine Learning.
By following along with the lessons in these books you will gain the knowledge and insight needed to be able to develop different Python applications and discover ML concepts.
You will be given daily lessons and projects to follow along with so that by the end of 7 days you will be able to understand all of the basics of programming with Python and you can start working on your projects in no time!
Next, you will also discover what is the link between Python and Machine Learning, and learn how to use Python programming to create exciting ML programs. Machine Learning is on the rise and more and more companies are looking for people that understand the ins and outs of it. By learning ML concepts you will be putting yourself light years ahead of your peers. Plus by the time you finish all the books, you will have a portfolio of projects and knowledge to show employers.
Inside this bundle you will find:
- Python Dictionaries
- Python Functions
- How to write your Python Loops
- Lists, Tuples, Operators, and Strings
- Python encapsulation
- Object-Oriented Programming using Python
- Python CGI & GUI
- A program for coming up with a simple calculator using Python Language
- Types of ML
- Neural & Bayesian Networks
- ML Libraries
- Decision Trees
- ML Datasets
- The Perceptron
- Regression Analysis
- Soft Computing
…and many, many more amazing and interesting topics!
This book collection takes readers on a knowledge trip through solved examples, tips, tricks, and visualized content. It will not only create an appetite for more but also give readers what they need to know about all of this fantastic topics!
Python Programming for Beginners Introduction FIRST DAY Part 1: Introduction History of Python Basic Features of Python Common Programming Language Features of Python Summary Part 2: Installing Python Installing Python Installing Python in Linux Modes of Running Python Integrated Development Environment (IDE) Summary Part 3: Variables First Program in Python Variables Conventions When Naming Variables in Python Keywords and Identifiers in Python Programming Language Comments and Statements Statements in Python Multi-Line Python Statement Indentation in Python Comments in Pythons Multi-Line Comments Summary SECOND DAY Part 4: Data Types in Python Numbers Number Conversion Type Conversion Decimal in Python Fractions in Python Mathematics in Python Summary Part 5: Loops and Functions LOOPS if…else Flow Control Nested if Statements in Python range() function in Python Using for Loop with Else While Loop in Python Using While Loop with Else Python’s Break and Continue Continue Statement in Python Pass Statement in Python Functions in Python Calling a Function in Python Docstring Python Function Return Statement Random Function in Python Iterators Manually Iterating Through Items in Python Explaining the Loop Creating Custom Iterator in Python Infinite Iterators Closure Function in Python Projects 1.Implementing Simple Calculator in Python 2.Program to return factors of any integer Summary THIRD DAY Part 6: Variable Scope and Lifetime in Python Functions Function Types Keywords Arguments in Python Arbitrary Arguments Recursion in Python Python Anonymous Function Python’s Global, Local, and Nonlocal Python’s Global and Local Variable Python’s Nonlocal Variables Global Keyword in Python Creating Global Variables across Python Modules Python Modules Module Import Import Statement in Python Importing all names Module Search Path in Python Reloading a Module Dir() built-in Python function Python Package Summary Part 7: Lists in Python Nested Lists Accessing Elements from a List Nested List Indexing Python Negative Indexing Manipulating Elements in a List using the assignment operator Changing a range of items in a list Appending/Extending items in the List Removing or Deleting Items from a List Deleting Multiple Elements Using Empty List to Delete an Entire or Specific Elements Summary FOURTH DAY Part 8: Tuples in Python Negative Indexing Slicing Available Tuple Methods in Python Testing Membership in Tuple Inbuilt Python Functions with Tuple Accessing items in a string Deleting or Changing in Python Summary Part 9: Strings in Python String Operations String Iteration Membership Test in String String Formatting in Python Python’s Docstring Practice Exercise Part 10: Operators in Python Arithmetic Operators Practice Exercise Modulus Squaring and Cubing in Python Operators with String in Python Summary FIFTH DAY Part 11: Python Sets Creating a set Creating a Set from a List Removing Elements from a Set Using the pop() Method to Remove an Item from a Set Set Operations in Python Set Union Set Intersection Using intersection() Set Difference Set Symmetric Difference Superset and Subset Membership Tests in Sets Iteration Inbuilt Functions with Set Frozenset Python Summary Part 12: Python Dictionaries What is a Python Dictionary? How do Python Dictionaries Work? Creating a Python dictionary Accessing Items within the Python dictionary How to Change Values in a Python Dictionary How Do You Loop Through a Python Dictionary How Do You Check if a Key Exists in the Dictionary How Do You Determine the Number of Items in the Dictionary A list of Common Python Dictionary Methods Merits of a Dictionary in Python Demerits of a Python dictionary Data Structures in Python Dictionary Creating a Dictionary Accessing Elements from a Dictionary Add or Modify Dictionary Elements Removing/Deleting Elements from a Dictionary Dictionary Methods in Python Odd Items Only Dictionary Membership Test in a Dictionary Inbuilt Functions Practice Exercise Summary SIXTH DAY Part 13: Object-Oriented Programming in Python Object and Class in Python Syntax Object/Class Instantiation Methods Inheritance Encapsulation in Python Polymorphism Class Definition in Python Object Creation in Python Constructors Deleting Objects and Attributes Deleting the Entire Object Inheritance in Python Syntax Method Overriding in Python Inheritance in Multiple Form in Python Operator Overloading Making Class Compatible with Inbuilt Special Functions Using More Inbuilt Methods Operator + Overloading Comparison Operators Overloading Summary Part 14: File Management and Exception Handling in Python File Methods in Python Directory in Python Getting Current Directory in Python Changing Directory File or a Directory Renaming in Python Removing File or Directory in Python Errors and Exceptions Inbuilt Exceptions in Python Exception Handling in Python Handling an Exception by Catching the Exception in Python User Defined Exception Summary SEVENTH DAY Part 15: Memoization, Modules, and Packages Python Modules Module Import Import Statement in Python Importing All Names Module Search Path in Python Reloading a Module Dir() Built-In Python function Python Package Summary Part 16: Time and Date Getting Current Time and Date Understanding the Datetime Module Timestamp Printing Current Date Time Object Print Hour to Microsecond Datetime Object Print Year to the Minute Using Timedelta Getting Difference Between Two Timedelta Objects From Datetime Import Timedelta Duration in Seconds Format Datetime in Python From strptime() to datetime Summary Conclusion Python Crash Course Introduction Chapter 1: What is the Python Language? The Benefits of Python It is Easy to Work with It Has Lots of Power Many Libraries to Work With Easy to Read It is an OOP Language The Basics of the Python Language Python Keywords Naming Our Identifiers Control Flow Basics Python Comments Variables Operators Chapter 2: Everything You Need to Know to Install Python Installing On the Mac Operating System The Windows Operating System The Linux System Chapter 3: The Python Variables and Strings The Python Variables The Python Strings Chapter 4: Handling Python Operators, Tuples, and Lists The Python Operators Arithmetic Operators Comparison Operators Logical Operators Assignment Operators Understanding Tuples and Lists The Lists The Tuples Chapter 5: The Python Functions Chapter 5: The Python Functions Why are User Defined Functions So Important? Options for Function Arguments Writing a Function Chapter 6: Python as an OOP Language and Working with the Python Classes How to Write a Class Working with the Access Class Chapter 7: The Conditional Statements in Python The If Conditional Statements The If Else Conditional Statement The Elif Conditional Statement Chapter 8: The Python Loops Chapter 8: The Python Loops The While Loop Working with the For Loop The Nested Loop Chapter 9: Handling Your Own Exceptions Chapter 9: Handling Your Own Exceptions How to Raise An Exception How to Define My Own Exceptions Chapter 10: Python Encapsulation Chapter 10: Python Encapsulation The Getter and Setter Putting It All Together What to Keep In Mind Chapter 11: Python Databases & Dictionaries and How to Work with Them Chapter 11: Python Databases & Dictionaries and How to Work with Them The Python Database The Python Dictionaries Chapter 12: Working with GUI and CGI in This Language Chapter 12: Working with GUI and CGI in This Language Getting Familiar with GUI What is CGI? Conclusion Machine Learning for Beginners Introduction Chapter 1: Introduction to Machine Learning The Development of Machine Learning What is Machine Learning? Importance of Artificial Intelligence Applications of Machine Learning Chapter 2: Types of Machine Learning Supervised Learning Unsupervised Learning Reinforcement Learning Semi-supervised Machine Learning Feature Learning Sparse Dictionary Learning Anomaly Detection Association Rule Learning Chapter 3: Models of Machine Learning Decision Trees Neural Networks Bayesian Networks Support Vector Machine Model Optimization Chapter 4: Probabilistic Models Logical models Geometric models Probabilistic models Probabilistic Method Graphical models Bayesian Networks Decision Tree Classifiers Deep Deterministic Policy Gradient Random Field Techniques Stochastic Models Chapter 5: Soft Computing Components of Soft Computing Relationship between hyperplanes and support vectors How the delta rule finds the correct answer What is a Perceptron? Chapter 6: Data Mining Application of data mining in related fields Relationship between data mining and other research areas Main data mining software Patterns found in data Simple Statistical Methods Association rules Chapter 7: Machine Learning Datasets Data Learning Modeling Chapter 8: Machine Learning Vs Deep Learning Deep Learning Solving the problem through Machine Learning Points to note Chapter 9: Pros and Cons Limitations of Machine Learning Points to note on the benefits and limitations of Machine Learning Conclusion Python Machine Learning
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