Pinned Repositories
20-news-group-classification-using-naive-bayes-
algorithms
Minimal examples of data structures and algorithms in Python
amazon-sagemaker-examples
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
Bayesian-Statistics-Simulation
beginApps
C-Plus-Plus
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
Java
All Algorithms implemented in Java
Python
All Algorithms implemented in Python
statsmodels
Statsmodels: statistical modeling and econometrics in Python
TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners with Latest APIs
MLikelihood's Repositories
MLikelihood/amazon-sagemaker-examples
Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker
MLikelihood/C-Plus-Plus
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
MLikelihood/Java
All Algorithms implemented in Java
MLikelihood/Python
All Algorithms implemented in Python
MLikelihood/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners with Latest APIs
MLikelihood/Blackbird-Dataset
MLikelihood/cats
R package 1
MLikelihood/CheXNet-Keras
This project is a tool to build CheXNet-like models, written in Keras.
MLikelihood/CS661_LinearHashing
MLikelihood/data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
MLikelihood/Deep-Learning-21-Examples
《21个项目玩转深度学习———基于TensorFlow的实践详解》配套代码
MLikelihood/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
MLikelihood/grf
Generalized Random Forests
MLikelihood/hadoop
Mirror of Apache Hadoop
MLikelihood/incubator-mxnet
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
MLikelihood/lambda-refarch-imagerecognition
The Image Recognition and Processing Backend reference architecture demonstrates how to use AWS Step Functions to orchestrate a serverless processing workflow using AWS Lambda, Amazon S3, Amazon DynamoDB and Amazon Rekognition.
MLikelihood/MLikelihood.github.io
MLikelihood/nmt
TensorFlow Neural Machine Translation Tutorial
MLikelihood/opencv
Open Source Computer Vision Library
MLikelihood/pmtk3
Probabilistic Modeling Toolkit for Matlab/Octave.
MLikelihood/Python_Happy_Coding
MLikelihood/R-Packages-Development
MLikelihood/R_Package_1
practice
MLikelihood/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
MLikelihood/Semantic-Segmentation-Suite
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
MLikelihood/shiny
Easy interactive web applications with R
MLikelihood/spark
Mirror of Apache Spark
MLikelihood/Statistical-and-Machine-Learning-Methods-Python-Implementation
MLikelihood/tensorflow
Computation using data flow graphs for scalable machine learning
MLikelihood/tensorflow_cookbook
Code for Tensorflow Machine Learning Cookbook