Code Drip shares 5 tricks that will improve your Python experience.
Caleb Curry has everything you need to know to get started as a C++ Programming Software developer / Software engineer — starting off with the super basics and then to intermediate topics.
Time indexes are below the video so you can jump to the section you want.
1:09 – Intro
9:31 – Installing g++
15:37 – C++ Concepts
22:31 – More C++ Concepts
30:48 – Using Directive and Declaration
37:33 – Variable Declaration and Initialization
40:40 – Using Variables with cout
44:46 – User Input with cin
47:57 – Conventions and Style Guides
56:23 – Intro to Functions
1:01:28 – Intro to Creating Custom Functions
1:09:05 – Pow Function
1:13:13 – Creating Custom Functions
1:22:20 – Creating Void Functions
1:29:11 – Intro to C++ Data Types
1:37:17 – Integral Data Types and Signed vs Unsigned
1:44:38 – Integral Data Types, sizeof, limit
1:49:35 – char Data Type
2:02:21 – bool Data Type
2:06:54 – Floating Point Numbers
2:15:00 – Constant const, macro, and enum
2:21:00 – Numeric Functions
2:28:37 – String Class and C Strings
2:37:47 – get line for Strings
2:40:52 – String Modifier Methods
2:47:56 – String Operation Methods
2:54:36 – Literals
2:59:42 – Hex and Octal
3:04:06 – Operator Precedence and Associativity
3:11:53 – Reviewing Key Concepts
3:17:54 – Control Flow
3:27:32 – If Statement Practice
3:32:33 – Logical and Comparison Operators
3:42:27 – Switch Statement and Enum
3:51:00 – Intro to Loops
3:58:01 – For Loops (How to Calculate Factorial)
4:05:06 – While Loop and Factorial Calculator
4:12:29 – Do While Loop
4:20:04 – Break and Continue
4:25:14 – Conditional Operator
4:29:04 – Intro to Our App
4:33:00 – Creating a Menu
4:38:11 – Creating a Guessing Game
4:45:27 – Intro to Arrays and Vectors
4:54:15 – Working with Arrays
5:04:21 – Passing Arrays to Functions
5:11:11 – Fill Array from Input
5:20:42 – Using and Array to Keep Track of Guessing
5:25:55 – Intro to Vectors
5:33:00 – Creating a Vector
5:36:39 – Passing Vectors to Functions
5:39:55 – Refactor Guessing Game to Use Vectors
5:43:47 – STL Array
5:47:47 – STL Arrays in Practice
5:51:45 – Refactor Guessing Game to Use Templatized Array
5:55:13 – Array vs Vector vs STL Array
5:01:49 – Range Based for Loop
6:07:03 – Intro to IO Streams
6:15:45 – Writing to Files with ofstream
6:24:43 – Readings from Files with ifstream
6:31:13 – Saving High Scores to File
6:39:46 – Functions and Constructors
6:47:53 – Refactoring IO to Function Call and Testing
6:54:31 – Multidimensional Arrays and Nested Vectors
6:59:29 – Const Modifier
7:04:33 – Pass by Reference and Pass By Value
7:11:41 – Swap Function with Pass by Reference
7:14:27 – Intro to Function Overloading
7:19:35 – Function Overloading Examples
7:26:22 – Default Arguments
7:33:24 – Intro to Multifile Compilation
7:40:56 – Multifile Compilation
7:48:15 – Makefiles
7:54:44 – Creating a Simple Makefile
8:01:30 – Intro to Namespaces
8:05:33 – Creating a Namespace
8:10:24 – Intro to Function Templates
8:15:24 – Creating a Function Template
8:18:40 – Overloading Function Templates
8:23:18 – Intro to Object Oriented Programming
8:30:39 – Intro to Structs
8:35:59 – Creating a Struct
8:41:48 – Classes and Object
8:49:58 – Creating a Class
8:52:45 – Working with Objects
9:00:11 – Intro to Constructors
9:05:18 – Constructors and Destructors
9:09:53 – Encapsulation
9:15:40 – Getters and Setters
9:22:47 – Static Data Members
9:29:59 – Intro to Operator Overloading
9:34:07 – Operator Overloading == and +
9:41:13 – Overloading Insert and Extraction Operators
9:49:07 – Friend Functions and Operator Overloading
9:56:14 – Class Across Files
10:03:31 – Inheritance and Polymorphism
10:08:49 – Base Classes and Subclasses Inheritance
10:16:54 – Polymorphism
10:23:15 – Conclusion
Kalle Hallden built a trading bot in Python and gave it $1000 to trade with.
Watch what happened.
Siraj Raval shows off examples of machine learning apps from his students.
If you’re wondering about my stance on the recent controversies around Siraj, I recorded a Data Point about that.
Machine Learning powers almost every internet service we use these days, but it’s rare to find a full pipeline example of machine learning being deployed in a web app. In this episode, I’d like to present 5 full-stack machine learning demos submitted as midterm projects from the students of my current course. The midterm assignment was to create a paid machine learning web app, and after receiving countless incredible submissions, I’ve decided to share my favorite 5 publicly. I was surprised by how many students in the course had never coded before and to see them building a full-stack web app in a few weeks was a very fulfilling experience. Use these examples as a template to help you ideate on potential business ideas to make a positive impact in the world using machine learning. And if you’d like, be sure to reach out and support each of the students I’ve demoed here today in any way can you offer. They’ve been working their butts off. Enjoy!
Presentation notebook: https://colab.research.google.com/drive/1m5aLHPnwIhVX8zgMvZUtK4iG9xSaMbk8
- Example 1 (Medicine): Dermatitis Detection
- Example 2 (Entertainment): Script Generator
- Example 3 (Finance): Price Prediction
- Example 4 (Recruiting): Resume Scanner
- Example 5 (Security): Threat Detection
Kaggle tests out different automatic machine learning libraries on this live stream coding session.
Dani, a game developer, recently made a game and decided to train an AI to play it.
A couple of weeks ago I made a video “Making a Game in ONE Day (12 Hours)”, and today I’m trying to teach an A.I to play my game!
Basically I’m gonna use Neural Networks to make the A.I learn to play my game.
This is something I’ve always wanted to do, and I’m really happy I finally got around to do it. Some of the biggest inspirations for this is obviously carykh, Jabrils & Codebullet!
Siraj Raval explores generative modeling technology.
This innovation is changing the face of the Internet as you read this. It’s now possible to design automated systems that can write novels, act as talking heads in videos, and compose music.
In this episode, Siraj explains how generative modeling works by demoing 3 examples that you can try yourself in your web browser.
- Demo 1 (Generating Music): https://colab.research.google.com/notebooks/magenta/piano_transformer/piano_transformer.ipynb
- Demo 2 (Generating Faces):
- Demo 3 (Generating 3D Objects):
- Autoencoders explained:
- Generative Adversarial Networks explained:
- Sequence Models explained:
- Generative Modeling explained:
A bot is software that interacts with humans to do things like chat, make recommendations, book travel and more. This is the second of a two part series where Sam Basu shows us how to build bots. In this episode, Sam gives the bots he built in Part 1 a modern UI by using Telerik Conversational UI user controls.
In this episode of Visual Studio Toolbox, Arturo Nunez shows us the seamless integration of Visual Studio and Unity and how this makes you a much more productive game developer. You get the benefits of things like IntelliSense and full debugging support for your scripts, as well as Unity specific features like directly implementing Unity API messages in MonoBehavior scripts and the MonoBehavior wizard for adding method definitions.
(And for a limited time, you can take advantage of the Unity Pro and Visual Studio Professional Bundle, which includes Visual Studio Pro, Unity Pro, $50 in monthly Azure credits and more.)