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mkdocs.yml
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# Project information
site_name: 'Deep Learning Wizard'
site_description: 'Learn deep learning and deep reinforcement learning theories and code easily and quickly. Used by thousands of students and professionals from top tech companies and research institutions.'
site_author: 'Ritchie Ng'
site_url: 'https://www.deeplearningwizard.com/'
# Navigation
pages:
- Home: index.md
- About Us: about.md
- Reviews: review.md
- AI Pipeline: pipeline.md
- Consultancy: consultancy.md
- Deep Learning Tutorials (CPU/GPU):
- Introduction: deep_learning/intro.md
- Course Progression: deep_learning/course_progression.md
- Matrices: deep_learning/practical_pytorch/pytorch_matrices.md
- Gradients: deep_learning/practical_pytorch/pytorch_gradients.md
- Linear Regression: deep_learning/practical_pytorch/pytorch_linear_regression.md
- Logistic Regression: deep_learning/practical_pytorch/pytorch_logistic_regression.md
- Feedforward Neural Networks (FNN): deep_learning/practical_pytorch/pytorch_feedforward_neuralnetwork.md
- Convolutional Neural Networks (CNN): deep_learning/practical_pytorch/pytorch_convolutional_neuralnetwork.md
- Recurrent Neural Networks (RNN): deep_learning/practical_pytorch/pytorch_recurrent_neuralnetwork.md
- Long Short Term Memory Neural Networks (LSTM): deep_learning/practical_pytorch/pytorch_lstm_neuralnetwork.md
- Autoencoders (AE): deep_learning/practical_pytorch/pytorch_autoencoder.md
- Fully-connected Overcomplete Autoencoder (AE): deep_learning/practical_pytorch/pytorch_fc_overcomplete_ae.md
# - Fully-connected Undercomplete Autoencoder (AE): deep_learning/practical_pytorch/pytorch_fc_undercomplete_ae.md
# - Convolutional Overcomplete Variational Autoencoder (VAE): deep_learning/practical_pytorch/pytorch_autoencoder.md
# - Convolutional Overcomplete Adversarial Autoencoder (AAE): deep_learning/practical_pytorch/pytorch_autoencoder.md
# - Generative Adversarial Networks (GAN): deep_learning/practical_pytorch/pytorch_autoencoder.md
- Derivative, Gradient and Jacobian: deep_learning/boosting_models_pytorch/derivative_gradient_jacobian.md
- Forward- and Backward-propagation and Gradient Descent: deep_learning/boosting_models_pytorch/forwardpropagation_backpropagation_gradientdescent.md
- From Scratch Logistic Regression: deep_learning/boosting_models_pytorch/fromscratch_logistic_regression.md
- Learning Rate Scheduling: deep_learning/boosting_models_pytorch/lr_scheduling.md
- Optimization Algorithms: deep_learning/boosting_models_pytorch/optimizers.md
- Weight Initialization and Activation Functions: deep_learning/boosting_models_pytorch/weight_initialization_activation_functions.md
- Supervised Learning to Reinforcement Learning (RL): deep_learning/deep_reinforcement_learning_pytorch/supervised_to_rl.md
- Markov Decision Processes (MDP) and Bellman Equations: deep_learning/deep_reinforcement_learning_pytorch/bellman_mdp.md
- Dynamic Programming: deep_learning/deep_reinforcement_learning_pytorch/dynamic_programming_frozenlake.md
- Speed Optimization Basics Numba: deep_learning/production_pytorch/speed_optimization_basics_numba.md
- Additional Readings: deep_learning/readings.md
- Machine Learning Tutorials (CPU/GPU):
- Introduction: machine_learning/intro.md
- GPU DataFrames: machine_learning/gpu/rapids_cudf.md
- GPU/CPU Fractional Differencing: machine_learning/gpu/gpu_fractional_differencing.md
# - Linear Regression: machine_learning/gpu/rapids_cudf.md
# - Ridge Regression: machine_learning/gpu/rapids_cudf.md
# - Kalman Filter: machine_learning/gpu/rapids_cudf.md
# - Stochastic Gradient Descent: machine_learning/gpu/rapids_cudf.md
# - K-nearest Neighbours Classification: machine_learning/gpu/rapids_cudf.md
# - K-Means Clustering: machine_learning/gpu/rapids_cudf.md
# - Density-Based Spatial Clustering of Applications with Noise (DBSCAN): machine_learning/gpu/rapids_cudf.md
# - Singular Value Decomposition (SVD), Dimensionality Reduction: machine_learning/gpu/rapids_cudf.md
# - Principal Component Analysis (PCA), Dimensionality Reduction: machine_learning/gpu/rapids_cudf.md
# - Uniform Manifold Approximation and Projection (UMAP), Dimensionality Reduction: machine_learning/gpu/rapids_cudf.md
- Programming Tutorials:
- Introduction: programming/intro.md
- C++: programming/cpp/cpp.md
- Bash: programming/bash/bash.md
- Python: programming/python/python.md
- Javascript: programming/javascript/javascript.md
- Electron: programming/electron/electron.md
# - Matplotlib: programming/plotting/matplotlib.md
- Scalable Database Tutorials:
- Introduction: database/intro.md
- Cassandra Cluster Setup: database/setting_up_cluster.md
- News:
- Welcome: news/news.md
- Deep Learning Introduction, Defence and Science Technology Agency (DSTA) and NVIDIA, June 2019: news/defence_and_science_technology_agency_dsta_nvidia_talk_2016_06.md
- Oral Presentation for AI for Social Good Workshop ICML, June 2019: news/detect_waterbone_debris_ai_for_social_good_icml_2019_06.md
- IT Youth Leader of The Year 2019, March 2019: news/it_youth_leader_2019_03_11.md
- AMMI (AIMS) supported by Facebook and Google, November 2018: news/ammi_facebook_google_recap_2018_11_21.md
- NExT++ AI in Healthcare and Finance, Nanjing, November 2018: news/nanjing_next_nus_tsinghua_ai_finance_healthcare_2018_11_01.md
- Recap of Facebook PyTorch Developer Conference, San Francisco, September 2018: news/facebook_pytorch_devcon_recap_2018_10_02.md
- Facebook PyTorch Developer Conference, San Francisco, September 2018: news/facebook_pytorch_developer_conference_2018_09_05.md
- NUS-MIT-NUHS NVIDIA Image Recognition Workshop, Singapore, July 2018: news/nvidia_nus_mit_datathon_2018_07_05.md
- Featured on PyTorch Website 2018: news/deep_learning_wizard_1y_2018_06_01.md
- NVIDIA Self Driving Cars & Healthcare Talk, Singapore, June 2017: news/nvidia_self_driving_cars_talk_2017_06_21.md
- NVIDIA Inception Partner Status, Singapore, May 2017: news/deep_learning_wizard_nvidia_inception_2018_05_01.md
# Configuration
theme:
name: 'material'
custom_dir: 'theme'
language: 'en'
feature:
tabs: true
logo:
icon: 'whatshot'
palette:
primary: 'teal'
accent: 'teal'
font:
text: 'Roboto'
code: 'Roboto Mono'
favicon: './docs/assets/favicon.ico'
# Extensions
markdown_extensions:
- admonition
- codehilite:
linenums: false
- footnotes
- meta
- toc:
permalink: true
- pymdownx.arithmatex
- pymdownx.betterem:
smart_enable: all
- pymdownx.caret
- pymdownx.critic
- pymdownx.details
- pymdownx.emoji:
emoji_generator: !!python/name:pymdownx.emoji.to_svg
- pymdownx.inlinehilite
- pymdownx.magiclink
- pymdownx.mark
- pymdownx.smartsymbols
- pymdownx.superfences
- pymdownx.tasklist:
custom_checkbox: true
- pymdownx.tilde
# Equations
extra_javascript:
- 'https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-MML-AM_CHTML'
# Social
extra:
social:
- type: 'github'
link: 'https://github.com/ritchieng'
- type: 'facebook'
link: 'https://www.facebook.com/DeepLearningWizard/'
- type: 'linkedin'
link: 'https://www.linkedin.com/company/deeplearningwizard/'
disqus: 'deep-learning-wizard'
# Google Analytics
google_analytics:
- 'UA-122083328-1'
- 'auto'
# Copyright
copyright: 'Copyright © 2019 Deep Learning Wizard'