WebToolTip com Full Stack Deep Learning with Python 2026 | 084CE5F8EBF35D763DE007160889F6A0E156F28B

WebToolTip com Full Stack Deep Learning with Python 2026

Name	[ WebToolTip.com ] Full-Stack Deep Learning with Python (2026)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	522.2 MB
Total Files	71
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Hash	084CE5F8EBF35D763DE007160889F6A0E156F28B

/
Get Bonus Downloads Here.url	0.2 KB
/01 - Introduction/
01 - Full-stack landscape and strategy.mp4	6.5 MB
01 - Full-stack landscape and strategy.srt	8.7 KB
02 - Full-stack deep learning MLOps and MLflow.mp4	8.9 MB
02 - Full-stack deep learning MLOps and MLflow.srt	10.3 KB
03 - Prerequisites.mp4	890.7 KB
03 - Prerequisites.srt	1.1 KB
/.../02 - 1. An Overview of Full-Stack Deep Learning/
01 - Components Planning and data collection.mp4	8.5 MB
01 - Components Planning and data collection.srt	12.1 KB
02 - Components Model training and deployment.mp4	5.5 MB
02 - Components Model training and deployment.srt	7.1 KB
03 - Artifacts in full-stack deep learning.mp4	3.6 MB
03 - Artifacts in full-stack deep learning.srt	4.5 KB
04 - Tools Compute, orchestration, and experiments.mp4	6.0 MB
04 - Tools Compute, orchestration, and experiments.srt	7.8 KB
05 - Tools Versioning, labeling, and feature stores.mp4	5.1 MB
05 - Tools Versioning, labeling, and feature stores.srt	6.8 KB
06 - Tools Deep learning frameworks and debugging.mp4	5.7 MB
06 - Tools Deep learning frameworks and debugging.srt	7.1 KB
07 - Tools APIs, UIs, CICD, and monitoring.mp4	7.4 MB
07 - Tools APIs, UIs, CICD, and monitoring.srt	9.4 KB
/.../03 - 2. MLOps with MLflow/
01 - Machine learning operations (MLOps).mp4	8.9 MB
01 - Machine learning operations (MLOps).srt	10.1 KB
02 - Managing the ML lifecycle with MLflow.mp4	6.6 MB
02 - Managing the ML lifecycle with MLflow.srt	7.4 KB
03 - Setting up the environment on Google Colab.mp4	17.4 MB
03 - Setting up the environment on Google Colab.srt	9.5 KB
04 - Running MLflow and using ngrok to access the MLflow UI.mp4	13.5 MB
04 - Running MLflow and using ngrok to access the MLflow UI.srt	10.9 KB
/.../04 - 3. Model Training and Evaluation Using MLflow/
01 - Loading and exploring the EMNIST dataset.mp4	13.0 MB
01 - Loading and exploring the EMNIST dataset.srt	8.9 KB
02 - Logging metrics parameters and artifacts in MLflow.mp4	17.2 MB
02 - Logging metrics parameters and artifacts in MLflow.srt	13.0 KB
03 - Set up the dataset and data loader.mp4	8.9 MB
03 - Set up the dataset and data loader.srt	6.3 KB
04 - Configuring the image classification DNN model.mp4	11.3 MB
04 - Configuring the image classification DNN model.srt	8.2 KB
05 - Training a model within an MLflow run.mp4	12.4 MB
05 - Training a model within an MLflow run.srt	6.2 KB
06 - Exploring parameters and metrics in MLflow.mp4	11.5 MB
06 - Exploring parameters and metrics in MLflow.srt	9.6 KB
07 - Making predictions using MLflow artifacts.mp4	13.7 MB
07 - Making predictions using MLflow artifacts.srt	9.4 KB
08 - Preparing data for image classification using CNN.mp4	11.3 MB
08 - Preparing data for image classification using CNN.srt	6.6 KB
09 - Configuring and training the model using MLflow runs.mp4	16.9 MB
09 - Configuring and training the model using MLflow runs.srt	10.7 KB
10 - Visualizing charts metrics and parameters on MLflow.mp4	17.4 MB
10 - Visualizing charts metrics and parameters on MLflow.srt	12.0 KB
/.../05 - 4. Hyperparameter Tuning with Optuna/
01 - Setting up the objective function for hyperparameter tuning.mp4	15.5 MB
01 - Setting up the objective function for hyperparameter tuning.srt	10.8 KB
02 - Hyperparameter optimization with Optuna and MLflow.mp4	16.4 MB
02 - Hyperparameter optimization with Optuna and MLflow.srt	12.2 KB
03 - Identifying the best model.mp4	7.5 MB
03 - Identifying the best model.srt	5.3 KB
04 - Registering a model with the MLflow registry.mp4	7.7 MB
04 - Registering a model with the MLflow registry.srt	6.6 KB
/.../06 - 5. Model Deployment and Predictions/
01 - Setting up MLflow on the local machine.mp4	9.8 MB
01 - Setting up MLflow on the local machine.srt	9.1 KB
02 - Workaround to get model artifacts on local machine.mp4	5.4 MB
02 - Workaround to get model artifacts on local machine.srt	4.4 KB
03 - Deploying and serving the model locally.mp4	14.9 MB
03 - Deploying and serving the model locally.srt	10.6 KB
/07 - Conclusion/
01 - Summary and next steps.mp4	3.0 MB
01 - Summary and next steps.srt	3.4 KB
~Get Your Files Here !/
Bonus Resources.txt	0.1 KB
/.../Ex_Files_FullStack_Deep_Learning/ExerciseFiles/datasets/
emnist-letters-test.csv	28.6 MB
emnist-letters-train.csv	171.6 MB
/.../Ex_Files_FullStack_Deep_Learning/ExerciseFiles/
demo_01_EMNISTClassificationUsingDNN.ipynb	1.7 MB
demo_02_EMNISTClassificationUsingCNN.ipynb	1.6 MB
demo_03_ModelDeployment.ipynb	42.1 KB
Total files 71