node --version

Step 1

npm install -g powerbi-visuals-tools

 npm config set proxy http://proxy.company.com:8080
 npm config set https-proxy http://proxy.company.com:8080

pbiviz

Step 2

pbiviz --create-cert

C:\Users\YourUserName\AppData\Roaming\npm\node_modules\powerbi-visuals-tools\certs\PowerBICustomVisualTest_public.pfx.

Step 3

• Select Current User and click Next

• Select Place all certificates in the following store
• Click Browse...

• Select Trusted Root Certification Authorities
• Click OK
• Click Next (previous screen)

• Click Finish

• Click Yes

Step 4

Creating a new visual

pbiviz new MyVisualName

cd VisualName

npm install

Step 5

Running your visual

pbiviz start

Step 6

Viewing your visual in PowerBI

• Open https://msit.powerbi.com/ and log in with your Power BI account

• Go to Settings in the gear menu:

• Click on Developer
• Check the “Enable developer visual for testing” checkbox

• Go back to your Power BI and click on your desired report
• Find the Visualizations pane by clicking on “Edit report”
• Select the Developer Visual in the Visualizations pane:

• Select the visual in the report canvas
• Bind data like normal
• Begin developing your visual (make sure pbiviz start is running).

Step 7

Installing the D3 JavaScript library

npm install --save d3

npm install -D @types/d3

"externalJS": [
"node_modules/powerbi-visuals-utils-dataviewutils/lib/index.js",
],

"node_modules/d3/dist/d3.min.js"

interface Window {
    d3: typeof d3
}

private d3: typeof d3;

constructor(options: VisualConstructorOptions) {
            this.d3 = window.d3;

Step 8

Packaging your visual for distribution

pbiviz package

App Store:

Example Histogram Visual:

1. In the App Store, click the blue “GET IT NOW” button on a Power BI visual.
2. Read, understand, and agree to terms of use and privacy policy, etc.
3. Note which Microsoft account you are signed in as.
4. Click “Continue”
5. Wait for the website to take you to Power BI Visuals.
6. Click “Select to download Histogram Chart” (or a chart of your choosing).

1. Select the ellipsis from the visualizations pane.
2. Select “Import from file” or “Import from marketplace” from the menu. (Take note of the “Caution: Import Custom Visual” warning: Custom visuals may be provided by third parties and could contain security or privacy risks. Only import from trusted authors and sources.)
3. Select the custom visual file (.PBIVIZ) in the folder you downloaded it to, then select Open.
4. The visual will appear as a new icon in the visualizations pane. Select it to create the visual on the report canvas.

RNN on Windows 10: Docker

Step 0) Prerequisites

• Docker CLI. To set up your local computer as a Docker host and access the Docker CLI commands, install Docker Engine before starting this workshop. https://docs.docker.com/engine/installation/
• Windows. This workshop contains screenshots from a Windows 10 Enterprise PC with the latest updates.
• Bash on Ubuntu on Windows is the preferred CLI for this workshop. https://www.windowscentral.com/how-install-bash-shell-command-line-windows-10

Step 1) Start Docker

Docker must be running with "Expose daemon on tcp://localhost:2375 without TLS" enabled. (Right click on the system tray icon then "Settings..."). This is not checked by default, so you must check it.

Step 2) Run Image

docker -v

docker run hello-world

export DOCKER_HOST=tcp://127.0.0.1:2375 

docker run -it saelia/rnn-js /bin/bash

Step 3) Sample Text

th sample.lua -gpu -1 -checkpoint cv/checkpoint_12900.t7 -length 150 -temperature .7

Sample Flags

Shutting Down

PLEASE see this previous blog post for important information and prerequisites before continuing!

Step 1) Preprocess

python scripts/preprocess.py --input_txt data/tiny-shakespeare.txt --output_h5 data/tiny-shakespeare.h5 --output_json data/tiny-shakespeare.json

Total vocabulary size: 65
Total tokens in file: 1115394
  Training size: 892316
  Val size: 111539
  Test size: 111539
Using dtype <type 'numpy.uint8'>

Preprocessing Flags

• --input_txt: Path to the text file to be used for training.
  • Default is the tiny-shakespeare.txt dataset.
• --output_h5: Path to the HDF5 file where preprocessed data should be written.
• --output_json: Path to the JSON file where preprocessed data should be written.
• --val_frac: What fraction of the data to use as a validation set; default is 0.1.
• --test_frac: What fraction of the data to use as a test set; default is 0.1.
• --quiet: If you pass this flag then no output will be printed to the console.

Step 2) Train

th train.lua -input_h5 data/tiny-shakespeare.h5 -input_json data/tiny-shakespeare.json -gpu -1

time th train.lua -gpu -1 -input_h5 data/tiny_shakespeare.h5 -input_json data/tiny_shakespeare.json -max_epochs 25 -print_every 10 -checkpoint_every 100 -batch_size 1 -seq_length 50

Training Flags

Data options:

• -input_h5, -input_json: Paths to the HDF5 and JSON files output from the preprocessing script.
• -batch_size: Number of sequences to use in a minibatch; default is 50.
• -seq_length: Number of timesteps for which the recurrent network is unrolled for backpropagation through time.

• -batch_size 1 -seq_length 50

Model options:

• -init_from: Path to a checkpoint file from a previous run of train.lua. Use this to continue training from an existing checkpoint; if this flag is passed then the other flags in this section will be ignored and the architecture from the existing checkpoint will be used instead.
• -reset_iterations: Set this to 0 to restore the iteration counter of a previous run. Default is 1 (do not restore iteration counter). Only applicable if -init_from option is used.
• -model_type: The type of recurrent network to use; either lstm (default) or rnn. lstm is slower but better.
• -wordvec_size: Dimension of learned word vector embeddings; default is 64. You probably won't need to change this.
• -rnn_size: The number of hidden units in the RNN; default is 128. Larger values (256 or 512) are commonly used to learn more powerful models and for bigger datasets, but this will significantly slow down computation.
• -dropout: Amount of dropout regularization to apply after each RNN layer; must be in the range 0 <= dropout < 1. Setting dropout to 0 disables dropout, and higher numbers give a stronger regularizing effect.
• -num_layers: The number of layers present in the RNN; default is 2.

Optimization options:

• -max_epochs: How many training epochs to use for optimization. Default is 50.
• -learning_rate: Learning rate for optimization. Default is 2e-3.
• -grad_clip: Maximum value for gradients; default is 5. Set to 0 to disable gradient clipping.
• -lr_decay_every: How often to decay the learning rate, in epochs; default is 5.
• -lr_decay_factor: How much to decay the learning rate. After every lr_decay_every epochs, the learning rate will be multiplied by the lr_decay_factor; default is 0.5.

Output options:

• -print_every: How often to print status message, in iterations. Default is 1.
• -checkpoint_name: Base filename for saving checkpoints; default is cv/checkpoint. This will create checkpoints named - cv/checkpoint_1000.t7, cv/checkpoint_1000.json, etc.
• -checkpoint_every: How often to save intermediate checkpoints. Default is 1000; set to 0 to disable intermediate checkpointing. Note that we always save a checkpoint on the final iteration of training.

Benchmark options:

• -speed_benchmark: Set this to 1 to test the speed of the model at every iteration. This is disabled by default because it requires synchronizing the GPU at every iteration, which incurs a performance overhead. Speed benchmarking results will be printed and also stored in saved checkpoints.
• -memory_benchmark: Set this to 1 to test the GPU memory usage at every iteration. This is disabled by default because like speed benchmarking it requires GPU synchronization. Memory benchmarking results will be printed and also stored in saved checkpoints. Only available when running in GPU mode.
• Backend options:
• -gpu: The ID of the GPU to use (zero-indexed). Default is 0. Set this to -1 to run in CPU-only mode
• -gpu_backend: The GPU backend to use; either cuda or opencl. Default is cuda.

Step 3) Sample

th sample.lua -gpu -1 -checkpoint cv/checkpoint_900.t7 -length 250 -temperature 0.7

Sampling Flags

• -checkpoint: Path to a .t7 checkpoint file from train.lua
• -length: The length of the generated text, in characters.
• -start_text: You can optionally start off the generation process with a string; if this is provided, the start text will be processed by the trained network before we start sampling. Without this flag, the first character is chosen randomly.
• -sample: Set this to 1 to sample from the next-character distribution at each timestep; set to 0 to instead just pick the argmax at every timestep. Sampling tends to produce more interesting results.
• -temperature: Softmax temperature to use when sampling; default is 1. Higher temperatures give noisier samples. Not used when using argmax sampling (sample set to 0).
• -gpu: The ID of the GPU to use (zero-indexed). Default is 0. Set this to -1 to run in CPU-only mode.
• -gpu_backend: The GPU backend to use; either cuda or opencl. Default is cuda.
• -verbose: By default just the sampled text is printed to the console. Set this to 1 to also print some diagnostic information.

Step 1) Windows 10

• Bash on Ubuntu on Windows is the preferred CLI for this workshop. We’ll be doing everything in the terminal – if you’ve never used the command-line, it would be good to learn a bit more about how that works before attempting this install. https://www.windowscentral.com/how-install-bash-shell-command-line-windows-10

Step 2) Docker

Step 3): Install Bash

Step 4) Install Torch

git clone https://github.com/torch/distro.git ~/torch --recursive

cd ~/torch

bash install-deps;

./install.sh

source ~/.bashrc

th

Step 5) Install HDF5 Library for Lua

cd ~/

sudo apt-get -y install python2.7-dev

sudo apt-get install libhdf5-dev

sudo apt-get install python-virtualenv

Step 6) Clone Torch-rnn

git clone https://github.com/jcjohnson/torch-rnn.git

# Install most things using luarocks

luarocks install torch 

luarocks install nn 

luarocks install optim 

luarocks install lua-cjson 

# We need to install torch-hdf5 from GitHub

cd ..

git clone https://github.com/deepmind/torch-hdf5 

cd torch-hdf5

luarocks make hdf5-0-0.rockspec

Step 7) Install HDF5 Library for Python

sudo apt install python-pip

sudo pip install -r requirements.txt

sudo pip install h5py

python
 import h5py

Next Steps:

If you want to actually train a model, continue reading here: A Whirlwind Tour of Recurrent Neural Networks (the hard way)

If you want to call a pre-trained model, continue reading here: A Whirlwind Tour of RNNs with Docker (the easy way)

Step 8) *OPTIONAL*:  Install CUDA Support

1. curl http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_9.1.85-1_amd64.deb

2. sudo dpkg -i cuda-repo-ubuntu1604_9.1.85-1_amd64.deb

3. sudo apt-key adv --fetch-keys http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub

4. sudo apt-get update

5. sudo apt-get install cuda

luarocks install cutorch

git config --global user.email "you@example.com"

git config --global user.name "Your Name"

Next Steps:

If you want to actually train a model, continue reading here: A Whirlwind Tour of Recurrent Neural Networks (the hard way)

If you want to call a pre-trained model, continue reading here: A Whirlwind Tour of RNNs with Docker (the easy way)

SEE THE FINISHED GAME

GETTING STARTED

CREATE A NEW PROJECT

Increasing diversity in games and the STEM fields is my passion. I was honored to join Dave Voyles for an interview about who I am, what I do in my career and my community, and the website I use to transcribe mu interviews with women who build video games, www.shebuildsgames.com. 

As an undergrad, I founded the Ada Lovelace Club for Women in Computer Science at Central Washington University, which is still going strong today. I fund-raised and organized a club field trip to the Grace Hopper Celebration of women in computing Conference. Because of my professional and friendly attitude, I was hired at Microsoft as a Technical Evangelist soon after I graduated. This process also tested my ability to be flexible, understanding, and patient in a changing environment, because my in-person interviews (in Chicago) had to take place immediately after my semester finals!

After moving to Chicago, I co-founded the Voxelles: Chicago's Women in Game Development. I cherished opportunities to guest-lecture organizations like Girls Make Games, Girls Who Code, and several high schools & colleges about game development and tech.

At last year's Game Developers Conference (GDC), I was accepted as an International Game Developers Association (IGDA) volunteer, where I provided support for the recruitment effort at their booth. The year before, I attended as a volunteer for Microsoft, and helped answer attendees' questions at the Xbox booth. Both years, I enthusiastically attended the Women in Gaming Luncheon presented by Xbox. I have kept my in-person and online communication skills sharp as I organized roadshows with Unity in Chicago, ran 4 game jams with the Voxelles, and sponsored Global Game Jam through Microsoft.

Like I said in the video interview with Dave, embedded above, "I want all the girls who follow in my footsteps to believe that they are Strong Female Characters. They can be the protagonists of their own life video games."

How to install the tools:

1. You only need to download one of these three files.
2. Each contains the full Ren'Py software development kit, with everything needed to develop Ren'Py games for Windows XP and up, Mac OS X 10.6 and up, and Linux x86/x86_64.
3. The development environment contains the files needed to produce games for all three platforms, the Ren'Py tutorial, and "The Question", an example game.
4. Ren'Py is free to download and use for commercial and non-commercial purposes. It may be modified and distributed under the terms of its license.

Using the Ren'Py Quickstart:

What is Ren'Py?

Sample Code

Writing Dialog

# A label statement names a place in the program.
# In this case, we're naming a place "start." 
# The "start" label marks the place a game begins running.

label start:

 "Wow, it's really dark in here."

# A say statement begins and ends with a double-quote.
# To include a double-quote (") in a string, type \".
# A single string on a line by itself is said by the narrator.

 "Lucy" "Better watch out."
 l "You don't want to be eaten by a Grue."

# Two strings separated by a space means the first string is
# used as a character's name, and the second is their message.
# This 2-argument form of the say statement is used for dialog,
# where a character is speaking out loud.

# Preserve the spacing before lines, aka indentation. 
# Indentation is used to group lines of script into blocks.

# Here's an example Character definition:

define l = Character(_("Lucy"), color="#ffcccc")

# Begins with the word "define," signifying we are defining something.
# Define is followed by a short name for the character, like "l."
# We'll be able to use that short name when writing dialog.
# This is followed by an = and the thing we're defining: a Character.
# Short names are case-sensitive. Capital L is a different name
# from lower-case l, so you'll need to be careful about that.

Adding Images

# Before showing images, first put the image files in the game directory.
# They should be placed at the start of the file, with no indentation.

image bg cave = "cave.jpg"
image lucy happy = "lucy_happy.png"
image lucy mad = "lucy_mad.png"

# Here are some sample image definitions. They should be placed at 
# the start of the file, without any indentation.
# Keyword image, followed by an image name (a space-separated list of words).
# The first word in the image name is the image tag. 
# For the first image, the tag is "bg," and for others, it's "lucy."

label start:

 scene bg cave
 show lucy happy

 l "Now that the lights are on..."

 show lucy mad at right

 l "What's the big idea?!"

# Two new statements: the scene and show statement.
# The scene statement clears the screen, then adds a background image.
# The show statement adds a background image on top of all other images.
# If there was already an image with the same tag, the new image
# would be used to replace the old one.
# The second show statement has an at clause, which gives a location.
# Common locations are left, right, and center, but you can define more.

 show logo base at logopos behind eileen
# This shows an image named logo base, shown at a user-defined position.
# It is also specified to be shown behind another image, eileen.
 
 hide logo
# This is the hide statement, which hides the image with the given tag.
# The show statement replaces an image.
# The scene statement clears the screen.
# The hide statement is used when something leaves before scene is over.

Transitions

# Here's some sample code showing how we include transitions in-game.

 scene bg whitehouse
 with Dissolve(.5)

 pause .5

 scene bg washington
 show eileen happy
 with Dissolve(.5)

# This uses the with statement. The with statement causes the scene to 
# transition from the last things shown to the things currently shown.
# It takes a transition as an argument (in this case, Dissolve).
# This transition takes an argument of an amount of time.
# In this case, each transition takes half a second (.5).

define slowdissolve = Dissolve(1.0)

# Define a short name for a transition using a define statement. 

 scene bg whitehouse
 with slowdissolve

 scene bg washington
 show eileen happy
 with slowdissolve

# Ren'Py defines some transitions for you, like Dissolve, Fade, & Move.

Music and Sound

# Ren'Py breaks up sound into channels. The channel a sound is played on
# determines if the sound loops or if it's saved & restored with the game.
# When a sound is played on the music channel, it is looped & saved.
# When played on the sound channel, it is played once and then stopped.
# Ren'Py supports the Ogg Vorbis, mp3, mp2, and wav file formats.

 play music "sunflower-slow-drag.ogg" fadeout 1
 queue music "sunflower-slow-drag.ogg"

# The play music command replaces the currently playing music, 
# and replaces it with the named filename.
# If you specify the currently playing song, it will restart it.
# The fadeout clause fades out the current music before starting new music. 
# The queue statement also adds music to the named channel, but it waits
# until the currently playing song is finished before playing new music.

 stop music fadeout 1
# The third statement is the stop statement. It stops the music playing
# on a channel. It also takes the fadeout clause. 

 play sound "tower_clock.ogg"
# The sound channel causes it to play only once. 

 queue sound "tower_clock.ogg"
 queue sound "tower_clock.ogg"
 queue sound "tower_clock.ogg"
# You can queue up multiple sounds on the sound channel, 
# but they will only play one at a time.
# Ren'Py has separate mixers for sound, music, and voices.

In-Game Menus and Python

# Menus are introduced by the menu block statement.
# The menu statement takes an indented block, in which
# each line must contain a choice in quotes.
# The choices must end with a colon, as each choice has its
# own block of Ren'Py code run when that choice is selected.

menu:
 "Yes, I do.":
  jump choice1_yes
 "No, I don't.":
  jump choice1_no

# Here, each block jumps to a label. While you could put small
# amounts of Ren'Py code inside a menu label, it's probably a 
# best practice to usually jump to a bigger block of code. 
# See three labels here: choice1_yes, choice1_no, choice1_done.
# When the first menu is picked, we jump to choice1_yes,
# which runs 2 lines of script before jumping to choice1_done.

label choice1_yes:
 $ menu_flag = True
 e "While creating a multi-path game can be a bit more work..."
 jump choice1_done

# Picking the second option jumps to choice1_no.
# Lines that start with $ are Python used to set a flag
# based on the user's choice. The flag is named menu_flag.
# menu_flag is set to True orFalse based on the user's choice.
# if statements can be used to test a flag, 
# so the game can remember the user's choices.

label choice1_no:
 $ menu_flag = False
 e "Games without menus are called kinetic novels..."
 jump choice1_done

label choice1_done:
 # ... the game continues here.

# Here's an example that shows how we can test a flag,
# and do different things if it's true or not. 

if menu_flag:
 e "For example, I remember that you plan to use menus"
else: 
 e "For example, I remember that you're not using menus"

Screen Positions

Animation and Transformation

# Moving images around the screen is called a Transform.
# Animation and Transformation Language (ATL) does this in Ren'Py.
# Animation is when the displayable being shown changes, like below: 

image eileen animated:
 "eileen vhappy"
 pause .5
 "eileen happy"
 pause .5
 repeat
# (You can only have one repeat statement per block.)
# The first place ATL can be used is as part of an image statement. 
# Instead of a 'displayable,' an image may be defined as ATL code.
# When used this way, be sure ATL includes displayables to actually show.

transform topright:
 xalign 1.0 yalign 0.0

# The 2nd way is through the transform statement. This assigns the ATL
# block of code to a python variable, allowing it to be used in and 
# at clauses and inside other transforms. 

 show logo base:
  xalign .3 yalign .7
  linear 1.0 xalign .7 yalign .3
  linear 1.0 xalign .3 yalign .7
  repeat
# Thirdly, an ATL block can be used as part of a show statement.

image eileen animated twice:
 "eileen vhappy"
 pause .5
 "eileen happy"
 pause .5
 repeat 2
# Writing 'repeat 2' makes the animation loop twice, then stop.

image eileen animated once:
 "eileen vhappy"
 pause .5
 "eileen happy"
# Omitting the repeat statement makes the animation stop after the end.

image bg atl transitions:
 "bg washington" with dissolve
 pause 1.0
 "bg whitehouse" with dissolve
 pause 1.0
 repeat
# Displayables are replaced instantaneously. We can use a 'with' clause
# to give a transition between displayables. 

transform move_jump:
 xalign 1.0 yalign 0.0
 pause 1.0
 xalign 0.0
 pause 1.0
 repeat
# This code starts the image off at the top-right of the screen, 
# waits one second, then moves it to the left side, waits 1 sec. Repeat.

transform move_slide:
 xalign 1.0 yalign 0.0
 linear 3.0 xalign 0.0
 pause 1.0
 repeat

 show bg band:
  xpos 0 ypos -222 xanchor 0 yanchor 0
  linear 5.0 xpos -435 ypos 0

# Along with xalign and yalign, Ren'Py supports the xpos, ypos, 
# xanchor, and yanchor properties. 
# We can pan around an image by using xpos and ypos to position images
# off of the screen. This usually means giving them negative positions.

 show logo base:
  zoom 1.0
  linear 1.0 zoom 1.5
  linear 1.0 zoom 1.0
  repeat
# The zoom property lets us scale the displayable by a factor, making it
# bigger and smaller. Zoom should always be greater than 0.5.

 show logo base:
  xzoom 0.75 yzoom 1.25
  linear 1.0 xzoom 1.25 yzoom 0.75
  linear 1.0 xzoom 0.75 yzoom 1.25
  repeat
# The xzoom and yzoom properties allow the displayable to be scaled 
# in the X and Y directions independently (squashed and stretched).

 show logo base:
  size (300, 450)

# The size property can set a size, in pixels, to scale the displayable.

 show logo base:
  alpha 1.0
  linear 1.0 alpha 0.0
  linear 1.0 alpha 1.0
  repeat
# The alpha property varies the opacity of a displayable.

 show logo base:
  xpos 0.5 ypos 0.5 xanchor 0.5 yanchor 0.5
  rotate 0
  linear 4.0 rotate 360
  repeat
# The rotate property lets us rotate a displayable.

 show bg washington:
  crop (0, 0, 800, 600)
  size (800, 600)
 
  linear 4.0 crop (350, 300, 400, 300)

# The crop property crops a rectangle out of a displayable, showing only
# part of it. When used together, they can be used to focus in on 
# specific parts of an image. 

 show eileen happy:
  right
  pause 1.25
  left
  pause 1.25
  repeat
# We can use left, right, and center inside of an ATL block of code.

 show logo base:
  xalign 0.0 yalign 0.0
  block:
   linear 1.0 xalign 1.0
   linear 1.0 xalign 0.0
   repeat
  time 11.5
  linear 0.5 xalign 1.0

 show logo base:
  parallel:
   linear 1.0 xalign 0.0
   linear 1.0 xalign 1.0
   repeat
  parallel:
   linear 1.3 yalign 1.0
   linear 1.3 yalign 0.0
   repeat
# The parallel statement runs two blocks of ATL code at the same time.
# Here, the top block moves the image in the horizontal direction, and
# the bottom block moves it in the vertical direction. 
# Since they're moving at different speeds, it looks like the image
# is bouncing on the screen. 

 show logo base:
  choice:
   linear 1.0 xalign 0.0
  choice: 
   linear 1.0 xalign 1.0
   repeat
# The choice statement makes Ren'Py randomly pick a block of ATL code.

MiniGames

Installing the Tools

Windows

• For the Windows platform, you will need to have the following minimum setup:
  • 64bit Intel compatible Dual Core CPU
  • 2GB RAM
  • DX11 compliant graphics card
  • Microsoft 64bit Windows 7 or higher
  • At least 3GB free Hard Disk space
• However, the recommended specifications are:
  • 64bit Intel compatible Quad core CPU
  • 8GB RAM
  • DX11 based graphics card
  • Microsoft 64bit Windows 10
  • SSD Hard Disk

Mac OS

• For the Mac OS platform, you will need to have the following minimum specs:
  • Mac OSX El Capitan or higher
  • An Intel Dual Core i3 processor
  • 4GB or more RAM
  • Xcode 7 or higher
• However, the recommended specifications are:
  • macOS
  • An Intel Quad Core i5 processor
  • 8GB RAM
  • SSD Hard Disk

Trial

Login

Make Games, Not Excuses!

Tutorials

• Chapter 1 - Movement
• Chapter 2 - Shooting
• Chapter 3 - Enemies
• Chapter 4 - Tiles and Views
• Chapter 5 - Scoring
• Chapter 6 - Sounds
• Chapter 7 - Title Screen
• Chapter 8 - Spawners

Create a New Project

• New Drag and Drop Project: This will create a new project in which the Object Editor (and any other editors that permit code) will be set up to use the GameMaker Studio 2 Drag and Drop (DnD) interface. Note that this is not an exclusive DnD interface, and you can switch between DnD and GML code by right-clicking your mouse.
• New GameMaker Language Project: This will create a project where the default programming is done using the GameMaker Language (GML). This is also not an exclusive GML interface, and you can switch between GML code and DnD by right-clicking your mouse.

Sprites

Animation

//Walking animation 
if (speed > 0)
{sprite_index = spr_player_walking;
image_speed = 0.5;}
else
{sprite_index = spr_player;}

//Shooting animation
sprite_index = spr_player_shooting;

Objects

Events and Code

1. Left: the action list - this gives a list overview of all the actions in the event
2. Middle: the action workspace - this is where you drop the actions that you want to perform and edit them
3. Right: the action toolbox - Here you can find all the Drag and Drop™ action blocks that you can use to create your games.

• if right arrow key down (vk_right): x + 4
• if left arrow key down (vk_left): x - 4
• if up arrow key down (vk_up): y - 4
• if down arrow key down (vk_down): y + 4

Rooms

• Layer Editor: Everything in a room is placed on layers. Layers are ordered by depth and this depth is what defines the order in which the layer contents will be rendered to the screen when the game runs. “Depth” is on somewhat of a Z-axis that can go up to 1000 and down to -1000. Projectiles should be underneath your protagonist layer, because you’re firing from the origin of your protagonist. You can always come back and edit the depth if you’re playing your game and something seems layered incorrectly.
• Layer Properties: Each layer that you add to the room will have its own properties, and those properties will change depending on the layer type.
• Room Properties: Rooms have a number of properties too, and these can be set here. Things like the room size and the camera view ports that are active can be set here.

• Background Layer
  • The background layer can be filled with a single color or a single image. It can be moved and positioned within the room, and you can have multiple background layers.
• Instance Layer
  • The instance layer is where you place all the instances of the objects that you require for the game.
• Tilemap Layer
  • Add tiles from any of the tile set resources you’ve created. This will be set up automatically to use a grid the size of the tile set cells. You can only add a single tile to each grid cell, so if you require multiple tiles to occupy the same space, then you should be using multiple tilemap layers.
• Path Layer
  • The path layer is the only one that does not actually get rendered when you run your game. This is more of a “convenience” layer for helping you to create or edit Path resources, since it permits you to add or edit paths within the actual room space.
• Asset Layer
  • The asset layer simply takes a sprite resource and draws it using the parameters that you set when you add it into the room. Sprites can be added to this layer by clicking on the sprite in the resource tree and then dragging it into the room editor workspace.

Creating Sounds

Compiling

Your First Game

Conclusion

• Microsoft Bot Framework Part 1: Getting Started
• Microsoft Bot Framework Part 2: Hello World
• Microsoft Bot Framework Part 3:  Conversation

• Intents – Verbs: What actions do you want your bot to take?
• Entities – Nouns: What things are your bots taking action on?
• Utterances – Example messages from the user that link intents and entities.

Create a LUIS Application

• I am interested to know about the product.
• I want to know about the product
• I would like to know about the product.

Implementing LUIS in Node.js

Code Sample: app.js

// Set up LUIS connection
var model = 'https://westus.api.cognitive.microsoft.com/luis/v2.0/apps/' + process.env.LUIS_ID + '?subscription-key=' + process.env.LUIS_KEY + '&verbose=true&timezoneOffset=0&q='
var recognizer = new builder.LuisRecognizer(model)
var dialog = new builder.IntentDialog({ recognizers: [recognizer] })
bot.dialog('/', dialog)
    // =========================================================
    // LUIS Dialogs
    // =========================================================
    .matches('WebNavigate', [
        function (session) {
            session.send(`You surf that web!`)
        }
    ])
var loop = false;
var count = 1;
dialog.matches('StartLoop', [
    function (session) {
        if (!loop) {
            loop = true;
            count = 1
            proactiveEmulation(session);
        }
    }
])
    .matches('Stop', [
        (session, response) => {
            session.send("Stopping loop.")
            loop = false;
        }
    ])
    .onDefault((session, results) => {
        session.send("Sorry, I did't understand that.")
        session.beginDialog('/', results)
    })

var proactiveEmulation = (session) => {
    if (loop) {
        session.send(`Hello, I am a web push notification! :) (${count++})
);
        setTimeout(() => proactiveEmulation(session), 5000);
    }
};

Conclusion

• https://www.slideshare.net/KevinLeung52/leveling-up-your-bot-with-language-intelligence
• http://github.com/KSLHacks/BotScheduleDemo

• Microsoft Bot Framework Part 1: Getting Started
• Microsoft Bot Framework Part 2: Hello World
• Microsoft Bot Framework Part 3:  Conversation