Jacob Cho's Data Science

*** Python Neural Networks with TensorFlow 9 : How to Install TensorFlow GPU on Linux # Add NVIDIA package repositories wget https://developer.download.nvidia.com... sudo dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb sudo apt-key adv --fetch-keys https://developer.download.nvidia.com... sudo apt-get update wget http://developer.download.nvidia.com/... sudo apt install ./nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb sudo apt-get update # Install NVIDIA driver sudo apt-get install --no-install-recommends nvidia-driver-410 # Reboot. Check that GPUs are visible using the command: nvidia-smi # Install development and runtime libraries (~4GB) sudo apt-get install --no-install-recommends \ cuda-10-0 \ libcudnn7=7.4.1.5-1+cuda10.0 \ libcudnn7-dev=7.4.1.5-1+cuda10.0 # Install TensorRT. Requires that libcudnn7 is installed above. sudo apt-get update && \ sudo apt-get install nvinfer-runtime-trt-repo-ubuntu1804-5.0.2-ga-cuda10.0 \

*** Python Neural Networks with TensorFlow 8 : Text Classification P4 - Saving the Model - Loading the Model - Making Predictions ***  Text-Based Tutorial: https://techwithtim.net/tutorials/pyt...

*** Python Neural Networks with TensorFlow 7 : Text Classification P3 - Validation Data - Training the Model - Testing the Model ***  Text-Based Tutorial: https://techwithtim.net/tutorials/pyt... *** About Train, Validation and Test Sets in Machine Learning ● Training Dataset - The sample of data used to fit the model. - The actual dataset that we use to train the model (weights and biases in the case of Neural Network). The model sees and learns from this data ● Validation Dataset - The sample of data used to provide an unbiased evaluation of a model fie on the training dataset while tuning model hyperparameters. The evaluation becomes more biased as skill on the validation dataset is incorporated into the model configuration. - The validation set is used to evaluate a given model, but this is for frequent evaluation. We as machine learning engineers use this data to fine-tune the model hyperparameters. Hence the model occasionally sees this data, b

*** Python Neural Networks with TensorFlow 6 : Text Classification P2, What is an Embedding Layer? - Understanding the Model Architecture Word Embedding Layer GlobalAveragePooling1D Layer Dense Layer ***  Text-Based Tutorial: https://techwithtim.net/tutorials/pyt...

*** Python Neural Networks with TensorFlow 5 : Text Classification P1 - Text Classification - Install Previous Version of Numpy - Loading Data (keras.datasets.imdb) - Integer Encoded Data - Preprocessing Data - Defining the Model ***  Text-Based Tutorial: https://techwithtim.net/tutorials/pyt...

*** Python Neural Network with TensorFlow 4 : Using the Model to Make Predictions - Using the Model - Prediction (.predict()) ***  Text-Based Tutorial: https://techwithtim.net/tutorials/pyt...

*** Python Neural Network with TensorFlow 3 : Creating a Model - Creating the Model (keras, 3 layers, 784 neurons) - Training the Model - Testing the Model ***  Text-Based Tutorial: https://techwithtim.net/tutorials/pyt...

*** Python Neural Network with TensorFlow 2 : TensorFlow 2.0 Tutorial - Loading & Looking Data - Installing TensorFlow 2.0 - Installing MatPlotLib - The Importance of Data - Keras Datasets (MNIST Fashion Dataset for Image Classsification) ***  Text-Based Tutorial: https://techwithtim.net/tutorials/pyt... ***  Tensorflow website: https://www.tensorflow.org/alpha/tuto...

*** Python Neural Network with tensorflow 1 : Whit is a Neural Network - Neural Network (신경망) ***  Text-Based Tutorial: https://techwithtim.net/tutorials/pyt...

*** Advanced Level Python Features 6 : Context Managers - Generators - With *** See also:  https://www.slideshare.net/Kevlin/python-advanced-building-on-the-foundation/19-Context_manager_anatomywith_Resource_as

*** Advanced Level Python Features 5 : Generators - Generators Functions - Generators Expressions *** See also:  https://mingrammer.com/translation-iterators-vs-generators/

*** Advanced level Python Features 4 : Decorators - Decorators *** See also:  https://medium.com/@preyansh.10607/decoding-the-mysterious-python-decorator-55b1b5e0c0e1

*** Advanced Level Python Features 3 : Metaclasses - Metaclasses - How Classes Really Work ***  More Info on Metaclasses: https://docs.python.org/3/reference/d... *** see also :  https://blog.ionelmc.ro/2015/02/09/understanding-python-metaclasses/

[ python v 2.7~ ] *** Advanced Level Python Features 2 : Special Methods & Data Model - Special Methods(Dunder(Double UNDERscore __)/Magic Methods) - Data Model ***  Data Model Documentation: https://docs.python.org/3/reference/d...

[ 이미지출처: DataFlair ] *** Advanced Level Python Features 1 : Overview of Python & How it Works - Metaclasses - Generators - Context Managers - Decorators - Others - When & Why Use These Features - Implementation

*** Python Machine Learning 12 : Implementing K-Means Clustering (using sklearn) - Importing Modules (numpy, sklearn/scale/load_digits/KMeans/metrics) - Loading the Data-set - Scoring - Training the Model ***  Text-Based Tutorial: https://techwithtim.net/tutorials/mac... ***  SkLearn Performance Evaluation: https://scikit-learn.org/stable/modul... ***  SkLearn Example Code: https://scikit-learn.org/stable/modul...

*** Python Machine Learning 11 : How K-Means Clustering Works - K-Means Clustering - Supervised vs. Unsupervised Algorithm - How K-Means Clustering Works ***  Text-Based Tutorial: https://techwithtim.net/tutorials/mac...

*** Python Machine Learning 10 : SVM P.3 - Implementing a SVM - Implementing a SVM - Adding a Kernel (linear, poly, rbf, sigmoid, precomputed) - Changing the Margin - Comparing to KNearestNeighbors ***  Text-Based Tutorial & Code Here: https://techwithtim.net/tutorials/mac... ***  SVC Docs: https://scikit-learn.org/stable/modul...

*** Python Machine Learning 9 : SVM P.2 - How SVM Work - What a SVM Does? - How A SVM Works - Hyper-planes - Picking a Hyper Plane - Margin - Kernels - What is a Kernels? - Soft & Hard Margin ***  Text-Based Tutorial & Code: https://techwithtim.net/tutorials/mac...

*** Python Machine Learning 8 : Support Vector Machines (SVM) : sklearn - Support Vector Machines (SVM) - Importing Modules (sklearn, svm, datasets) - Loading Data - Splitting ***  Text-Based Tutorial & Code: https://techwithtim.net/tutorials/mac...