Download Linkedin - Full-Stack Deep Learning with Python Torrent

Torrent Contents Size: 431.1 MB

Linkedin - Full-Stack Deep Learning with Python

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01 - Full-stack deep learning, MLOps, and MLflow.mp4	MP4	9.8 MB
01 - Full-stack deep learning, MLOps, and MLflow.srt	SRT	12.5 KB
01 - Introducing full-stack deep learning.mp4	MP4	7.8 MB
01 - Introducing full-stack deep learning.srt	SRT	11.4 KB
01 - Loading and exploring the EMNIST dataset.mp4	MP4	9.9 MB
01 - Loading and exploring the EMNIST dataset.srt	SRT	8.8 KB
01 - Preparing data for image classification using CNN.mp4	MP4	9.7 MB
01 - Preparing data for image classification using CNN.srt	SRT	6.9 KB
01 - Setting up MLflow on the local machine.mp4	MP4	8.2 MB
01 - Setting up MLflow on the local machine.srt	SRT	8.4 KB
01 - Summary and next steps.mp4	MP4	2.5 MB
01 - Summary and next steps.srt	SRT	3.2 KB
02 - Configuring and training the model using MLflow runs.mp4	MP4	15.5 MB
02 - Configuring and training the model using MLflow runs.srt	SRT	10.9 KB
02 - Introducing MLOps.mp4	MP4	6.6 MB
02 - Introducing MLOps.srt	SRT	7.6 KB
02 - Logging metrics, parameters, and artifacts in MLflow.mp4	MP4	11 MB
02 - Logging metrics, parameters, and artifacts in MLflow.srt	SRT	11 KB
02 - Prerequisites.mp4	MP4	898.8 KB
02 - Prerequisites.srt	SRT	1.1 KB
02 - Workaround to get model artifacts on the local machine.mp4	MP4	4.3 MB
02 - Workaround to get model artifacts on the local machine.srt	SRT	3.9 KB
03 - Deploying and serving the model locally.mp4	MP4	13.8 MB
03 - Deploying and serving the model locally.srt	SRT	10.6 KB
03 - Introducing MLflow.mp4	MP4	6.3 MB
03 - Introducing MLflow.srt	SRT	7.9 KB
03 - Set up the dataset and data loader.mp4	MP4	6.9 MB
03 - Set up the dataset and data loader.srt	SRT	6.4 KB
03 - Visualizing charts, metrics, and parameters on MLflow.mp4	MP4	15.2 MB
03 - Visualizing charts, metrics, and parameters on MLflow.srt	SRT	12 KB
04 - Configuring the image classification DNN model.mp4	MP4	10.5 MB
04 - Configuring the image classification DNN model.srt	SRT	8.7 KB
04 - Setting up the environment on Google Colab.mp4	MP4	13 MB
04 - Setting up the environment on Google Colab.srt	SRT	9.2 KB
04 - Setting up the objective function for hyperparameter tuning.mp4	MP4	12.4 MB
04 - Setting up the objective function for hyperparameter tuning.srt	SRT	9.8 KB
05 - Hyperparameter optimization with Hyperopt and MLflow.mp4	MP4	13.9 MB
05 - Hyperparameter optimization with Hyperopt and MLflow.srt	SRT	11.7 KB
05 - Running MLflow and using ngrok to access the MLflow UI.mp4	MP4	10.3 MB
05 - Running MLflow and using ngrok to access the MLflow UI.srt	SRT	9.7 KB
05 - Training a model within an MLflow run.mp4	MP4	11.1 MB
05 - Training a model within an MLflow run.srt	SRT	7 KB
06 - Exploring parameters and metrics in MLflow.mp4	MP4	9 MB
06 - Exploring parameters and metrics in MLflow.srt	SRT	7.9 KB
06 - Identifying the best model.mp4	MP4	7.8 MB
06 - Identifying the best model.srt	SRT	6 KB
07 - Making predictions using MLflow artifacts.mp4	MP4	11.4 MB
07 - Making predictions using MLflow artifacts.srt	SRT	8.8 KB
07 - Registering a model with the MLflow registry.mp4	MP4	5.7 MB
07 - Registering a model with the MLflow registry.srt	SRT	6 KB
Bonus Resources.txt	TXT	409.6 B
Get Bonus Downloads Here.url	URL	204.8 B
demo_01_EMNISTClassificationUsingDNN-checkpoint.ipynb	IPYNB	1.7 MB
demo_01_EMNISTClassificationUsingDNN.ipynb	IPYNB	1.7 MB
demo_02_EMNISTClassificationUsingCNN.ipynb	IPYNB	3.1 MB
demo_03_ModelDeployment-checkpoint.ipynb	IPYNB	46.3 KB
demo_03_ModelDeployment.ipynb	IPYNB	37.7 KB
emnist-letters-test.csv	CSV	27.3 MB
emnist-letters-train.csv	CSV	163.7 MB

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Linkedin - Full-Stack Deep Learning with Python

Torrent Contents Size: 431.1 MB

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