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001 Introduction.en.srt
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001 Introduction.mp4
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1
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002 What is a Model_.mp4
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002 What is a Model_.en.srt
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003 How do we create a Model_.en.srt
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003 How do we create a Model_.mp4
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004 Types of Machine Learning.en.srt
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004 Types of Machine Learning.mp4
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005 Creating a Spyder development environment.en.srt
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005 Creating a Spyder development environment.mp4
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006 Python NumPy Pandas Matplotlib crash course.en.srt
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006 python-np-pd-plt.zip
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006 Python NumPy Pandas Matplotlib crash course.mp4
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007 Building and evaluating a Classification Model.mp4
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111.7 MB
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007 git-hub-link.txt
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007 ml-classification.zip
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7
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008 Saving the Model and the Scaler.en.srt
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008 Saving the Model and the Scaler.mp4
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009 Predicting locally with deserialized Pickle objects.en.srt
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009 Predicting locally with deserialized Pickle objects.mp4
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009 use-model.zip
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010 Using the Model in Google Colab environment.en.srt
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010 Using the Model in Google Colab environment.mp4
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010 use-model-colab.zip
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011 Flask REST API Hello World.en.srt
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011 Flask REST API Hello World.mp4
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011 flask-hello-world.zip
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012 Creating a REST API for the Model.en.srt
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012 Creating a REST API for the Model.mp4
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012 classifier-rest-service.zip
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013 Signing up for a Google Cloud free trial.en.srt
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013 Signing up for a Google Cloud free trial.mp4
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014 Hosting the Machine Learning REST API on the Cloud.mp4
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014 classifier-rest-service-on-GCP.zip
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015 Deleting the VM instance.en.srt
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015 Deleting the VM instance.mp4
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016 Serverless Machine Learning API using Cloud Functions.en.srt
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016 Serverless Machine Learning API using Cloud Functions.mp4
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016 google-cloud-functions-serverless-ml.zip
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017 Creating a REST API on Google Colab.en.srt
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017 Creating a REST API on Google Colab.mp4
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017 colab-rest-api.zip
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018 Postman REST client.en.srt
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018 Postman REST client.mp4
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019 Understanding Deep Learning Neural Network.en.srt
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019 Understanding Deep Learning Neural Network.mp4
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020 Building and deploying PyTorch models.en.srt
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020 Building and deploying PyTorch models.mp4
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020 save-export-reload-pytorch-models.zip
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021 Creating a REST API for the PyTorch Model.mp4
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021 pytorch-flask.zip
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022 Saving & loading TensorFlow Keras models.mp4
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022 tf-serving-save-export.zip
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023 Understanding Docker containers.en.srt
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023 Understanding Docker containers.mp4
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024 Creating a REST API using TensorFlow Model Server.mp4
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024 tf-model-serving.zip
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025 Converting a PyTorch model to TensorFlow format using ONNX.mp4
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025 pytorch-create-save-onnx.zip
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026 Converting text to numeric values using bag-of-words model.en.srt
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026 Converting text to numeric values using bag-of-words model.mp4
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027 tf-idf model for converting text to numeric values.en.srt
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027 tf-idf model for converting text to numeric values.mp4
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028 Creating and saving text classifier and tf-idf models.en.srt
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028 Creating and saving text classifier and tf-idf models.mp4
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028 text-classifier.zip.zip
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029 Creating a Twitter developer account.mp4
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029 Creating a Twitter developer account.en.srt
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030 Deploying tf-idf and text classifier models for Twitter sentiment analysis.en.srt
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030 Deploying tf-idf and text classifier models for Twitter sentiment analysis.mp4
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030 twitter-sentiment-analysis.zip
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031 text-classifier-pytorch.zip
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031 Creating a text classifier using PyTorch.en.srt
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031 Creating a text classifier using PyTorch.mp4
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032 Creating a REST API for the PyTorch NLP model.mp4
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032 pytorch-nlp-rest.zip
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033 Twitter sentiment analysis with PyTorch REST API.mp4
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033 twitter-pytorch-rest.zip
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034 Creating a text classifier using TensorFlow.en.srt
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034 Creating a text classifier using TensorFlow.mp4
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034 text-classifier-tensorflow.zip
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035 Creating a REST API for TensforFlow models using Flask.en.srt
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035 Creating a REST API for TensforFlow models using Flask.mp4
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035 tf-nlp-flask-rest.zip
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036 tf-serverless.zip
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036 Serving TensorFlow models serverless.en.srt
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036 Serving TensorFlow models serverless.mp4
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037 Serving PyTorch models serverless.en.srt
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037 Serving PyTorch models serverless.mp4
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037 pytorch-serverless.zip
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038 TensorFlow.js introduction.en.srt
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038 TensorFlow.js introduction.mp4
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039 Installing Visual Studio Code and Live Server.en.srt
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039 Installing Visual Studio Code and Live Server.mp4
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040 JavaScript crash course (optional).en.srt
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040 JavaScript crash course (optional).mp4
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040 javascript-crash-course.zip
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041 Adding TensforFlow.js to a web page.en.srt
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041 Adding TensforFlow.js to a web page.mp4
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041 tfjs1.zip
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042 Basic tensor operations using TensorFlow.js.en.srt
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042 Basic tensor operations using TensorFlow.js.mp4
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042 tfjs2.zip
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043 Deploying Keras model on a web page using TensorFlow.js.en.srt
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043 Deploying Keras model on a web page using TensorFlow.js.mp4
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043 tfjs4.zip
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044 Deriving formula from a Linear Regression Model.en.srt
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044 Deriving formula from a Linear Regression Model.mp4
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044 linear-regression.zip
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045 Machine Learning Operations (MLOps).mp4
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046 MLflow Introduction.en.srt
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046 MLflow Introduction.mp4
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047 Tracking Model training experiments with MLfLow.en.srt
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047 Tracking Model training experiments with MLfLow.mp4
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047 ml-pipeline-mlfow.zip
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048 Why track ML experiments_.en.srt
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048 Why track ML experiments_.mp4
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049 Running MLflow on Colab.en.srt
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049 Running MLflow on Colab.mp4
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049 running-mlflow-on-colab.zip
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050 Tracking PyTorch experiments with MLflow.en.srt
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050 Tracking PyTorch experiments with MLflow.mp4
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050 mlflow-pytorch.zip
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051 Deploying Models with MLflow.en.srt
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051 Deploying Models with MLflow.mp4
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051 mlflow-deploy.zip
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TutsNode.com.txt
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[TGx]Downloaded from torrentgalaxy.to .txt
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