Download Free Download : Linkedin - Full-Stack Deep Learning with Python
mp4 | Video: h264,1280X720 | Audio: AAC, 44.1 KHz
Genre:eLearning | Language: English | Size:233.45 MB
Files Included :
01 - Full-stack deep learning, MLOps, and MLflow.mp4 (9.8 MB)
MP4
02 - Prerequisites.mp4 (898.79 KB)
MP4
01 - Introducing full-stack deep learning.mp4 (7.78 MB)
MP4
02 - Introducing MLOps.mp4 (6.62 MB)
MP4
03 - Introducing MLflow.mp4 (6.32 MB)
MP4
04 - Setting up the environment on Google Colab.mp4 (13.02 MB)
MP4
05 - Running MLflow and using ngrok to access the MLflow UI.mp4 (10.26 MB)
MP4
01 - Loading and exploring the EMNIST dataset.mp4 (9.94 MB)
MP4
02 - Logging metrics, parameters, and artifacts in MLflow.mp4 (11.05 MB)
MP4
03 - Set up the dataset and data loader.mp4 (6.9 MB)
MP4
04 - Configuring the image classification DNN model.mp4 (10.48 MB)
MP4
05 - Training a model within an MLflow run.mp4 (11.14 MB)
MP4
06 - Exploring parameters and metrics in MLflow.mp4 (9.04 MB)
MP4
07 - Making predictions using MLflow artifacts.mp4 (11.35 MB)
MP4
01 - Preparing data for image classification using CNN.mp4 (9.74 MB)
MP4
02 - Configuring and training the model using MLflow runs.mp4 (15.5 MB)
MP4
03 - Visualizing charts, metrics, and parameters on MLflow.mp4 (15.23 MB)
MP4
04 - Setting up the objective function for hyperparameter tuning.mp4 (12.36 MB)
MP4
05 - Hyperparameter optimization with Hyperopt and MLflow.mp4 (13.88 MB)
MP4
06 - Identifying the best model.mp4 (7.79 MB)
MP4
07 - Registering a model with the MLflow registry.mp4 (5.68 MB)
MP4
01 - Setting up MLflow on the local machine.mp4 (8.18 MB)
MP4
02 - Workaround to get model artifacts on the local machine.mp4 (4.27 MB)
MP4
03 - Deploying and serving the model locally.mp4 (13.76 MB)
MP4
01 - Summary and next steps.mp4 (2.47 MB)
MP4
MP4
02 - Prerequisites.mp4 (898.79 KB)
MP4
01 - Introducing full-stack deep learning.mp4 (7.78 MB)
MP4
02 - Introducing MLOps.mp4 (6.62 MB)
MP4
03 - Introducing MLflow.mp4 (6.32 MB)
MP4
04 - Setting up the environment on Google Colab.mp4 (13.02 MB)
MP4
05 - Running MLflow and using ngrok to access the MLflow UI.mp4 (10.26 MB)
MP4
01 - Loading and exploring the EMNIST dataset.mp4 (9.94 MB)
MP4
02 - Logging metrics, parameters, and artifacts in MLflow.mp4 (11.05 MB)
MP4
03 - Set up the dataset and data loader.mp4 (6.9 MB)
MP4
04 - Configuring the image classification DNN model.mp4 (10.48 MB)
MP4
05 - Training a model within an MLflow run.mp4 (11.14 MB)
MP4
06 - Exploring parameters and metrics in MLflow.mp4 (9.04 MB)
MP4
07 - Making predictions using MLflow artifacts.mp4 (11.35 MB)
MP4
01 - Preparing data for image classification using CNN.mp4 (9.74 MB)
MP4
02 - Configuring and training the model using MLflow runs.mp4 (15.5 MB)
MP4
03 - Visualizing charts, metrics, and parameters on MLflow.mp4 (15.23 MB)
MP4
04 - Setting up the objective function for hyperparameter tuning.mp4 (12.36 MB)
MP4
05 - Hyperparameter optimization with Hyperopt and MLflow.mp4 (13.88 MB)
MP4
06 - Identifying the best model.mp4 (7.79 MB)
MP4
07 - Registering a model with the MLflow registry.mp4 (5.68 MB)
MP4
01 - Setting up MLflow on the local machine.mp4 (8.18 MB)
MP4
02 - Workaround to get model artifacts on the local machine.mp4 (4.27 MB)
MP4
03 - Deploying and serving the model locally.mp4 (13.76 MB)
MP4
01 - Summary and next steps.mp4 (2.47 MB)
MP4
Code:
Bitte
Anmelden
oder
Registrieren
um Code Inhalt zu sehen!
Code:
Bitte
Anmelden
oder
Registrieren
um Code Inhalt zu sehen!
Code:
Bitte
Anmelden
oder
Registrieren
um Code Inhalt zu sehen!