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Data Science Model Deployments and Cloud Computing on GCP - Lab - Model Endpoint Deployment
In this lab video, you will learn how to deploy a custom-trained machine learning model to a production environment using Vertex AI. This clip is from the chapter "Vertex AI - Machine Learning Framework" of the series "Data Science Model...
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Data Science Model Deployments and Cloud Computing on GCP - Lab - Data Validation Using App Engine
In this lab video, we will explore how to use Google App Engine to perform data validation on user input. This clip is from the chapter "Data Science Models with Google App Engine" of the series "Data Science Model Deployments and Cloud...
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Data Science Model Deployments and Cloud Computing on GCP - Overview - Problem Statement
This video provides an overview of the problem statement. This clip is from the chapter "Data Science Models with Google App Engine" of the series "Data Science Model Deployments and Cloud Computing on GCP".This section focuses on data...
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Data Science Model Deployments and Cloud Computing on GCP - Introduction to ML Model Lifecycle
This video provides an introduction to the ML model lifecycle. This clip is from the chapter "Data Science Models with Google App Engine" of the series "Data Science Model Deployments and Cloud Computing on GCP".This section focuses on...
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Fundamentals of Neural Networks - Lab 1 - RNN in Text Classification
This video demonstrates how to design a recurrent neural network or RNN. This clip is from the chapter "Recurrent Neural Networks" of the series "Fundamentals in Neural Networks".This section explains NLP, we will start with recurrent...
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Fundamentals of Neural Networks - Lab 4 - Transfer Learning
This video demonstrates transfer learning. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural networks where you will start with image...
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Fundamentals of Neural Networks - Lab 2 - Introduction to CNN
This video demonstrates the architecture and how to carry out the code using TensorFlow in collab and building a convolutional neural network. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in...
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Harnessing Brain Power: Enhancing Agility and Memory
Dive into the fascinating world of brain agility and memory enhancement. Learn how repetitive activities like juggling can physically alter the brain, increasing gray matter in key areas. This video highlights the science behind brain...
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Microsoft Project 2021 From Beginners to Advanced - Create a Material Resource
In this video, we will learn to work with the Timeline view in Project 2021, create and customize timelines, add tasks and milestones to timelines, and format timelines to suit our requirements. This clip is from the chapter "Resources"...
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Chatbots Development with Amazon Lex - Module 2 Overview
This is an introductory video on the concepts to be learned in this module, including chatbot creation steps, AWS Lambda, Twilio, and project creation.
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Deep Learning - Crash Course 2023 - Training the Neural Network
In this video, you will learn about training the neural network by selecting the right hyperparameters, choosing the right optimization algorithm, and evaluating the performance of the model. This clip is from the chapter "Deep Learning...
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Deep Learning - Crash Course 2023 - Challenges in Creating Deep Neural Networks from Scratch
In this video, we will discuss the challenges involved in creating deep neural networks from scratch. We will explore the common issues faced during the training process and learn how to overcome them. This clip is from the chapter...
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Deep Learning - Crash Course 2023 - Confirming Universal Approximation Theorem Works
In this video, we will confirm the effectiveness of the Universal Approximation Theorem by implementing it on a practical problem. This clip is from the chapter "Universal Approximation Theorem" of the series "Deep Learning - Crash...
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Deep Learning - Crash Course 2023 - Data Standardization - 2
In this video, we will understand when and how to apply standard Scaler with data standardization. This clip is from the chapter "Sigmoid Neuron Implement with Python" of the series "Deep Learning - Crash Course 2023".In this section,...
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Deep Learning - Crash Course 2023 - Train Test Split
In this video, you will learn how to use Train_Test_Split on our dataset with Scikit-learn. This clip is from the chapter "MP Neuron in Python" of the series "Deep Learning - Crash Course 2023".In this section, you will learn how to...
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Deep Learning - Crash Course 2023 - Bias
In this video, you will learn about bias in neural networks. This clip is from the chapter "Getting the Basics Right" of the series "Deep Learning - Crash Course 2023".In this section, you will learn some basic terms used in deep learning.
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Advanced Chatbots with Deep Learning and Python - Vectorizing Train and Test Data
After creating the vectorization function, we will input the stories, queries, and answers using the vectorize function that we created using the train data.
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Advanced Chatbots with Deep Learning and Python - Generative Versus Retrieval Chatbots
In this lecture, you will learn about a generative and retrieval chatbot and compare the differences between the two chatbots.
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Recommender Systems Complete Course Beginner to Advanced - Basics of Recommender System: Data Partitioning
Here, we will look at data partitioning, represented as a URL.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Accuracy Versus Recommendations
We will now perform data visualization; we will check the accuracy of our recommender model with the recommendations.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Compute Loss
This is the next step of training our model, which entails the compute loss model.
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Recommender Systems Complete Course Beginner to Advanced - Project Amazon Product Recommendation System: Random Train-Test Split
After mapping the rating to the dataset, we will train-test split the dataset to our recommender system with shuffling and prediction.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Inference After Training
In this video, you will learn about the inference mechanisms for generic recommender systems, including training the system to capture information to make recommendations.
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Recommender Systems Complete Course Beginner to Advanced - Deep Learning Foundation for Recommender Systems: Deep Learning in Recommendation systems
As we are aware, recommender systems are migrating from machine learning to deep learning, the reason being to capture non-linear and non-trivial relationships.