Pluralsight - Learning Path - Deep Learning Literacy - Practical Application

Files Included :

1 Course Overview.mp4 (2.15 MB)
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1 Welcome!.mp4 (2.06 MB)
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2 The Power of Deep Learning.mp4 (4.2 MB)
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3 What Is Deep Learning.mp4 (9.29 MB)
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4 Advantages.mp4 (4.36 MB)
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5 Disadvantages.mp4 (4.34 MB)
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6 Case Study - Diagnostic Image Analysis.mp4 (8.51 MB)
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1 Module Overview.mp4 (825.9 KB)
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2 Introduction to Healthcare Data.mp4 (9.71 MB)
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3 Medical Coding.mp4 (6.02 MB)
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4 Document and Text Analysis.mp4 (6.54 MB)
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5 Image Analysis.mp4 (9.25 MB)
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6 Device Data.mp4 (8.25 MB)
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7 Case study - Automated Medical Coding.mp4 (8.67 MB)
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1 Module Overview.mp4 (567.44 KB)
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2 Decision Support vs Decision Making.mp4 (5.24 MB)
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3 Interpretability.mp4 (4.82 MB)
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4 Bias.mp4 (4.88 MB)
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5 Peer Review.mp4 (6.69 MB)
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6 Case study - Sepsis Algorithm.mp4 (5.26 MB)
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7 Course Summary.mp4 (618.51 KB)
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1 Course Overview.mp4 (3.1 MB)
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1 Course and Module Overview.mp4 (2.08 MB)
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2 What Are Recommendation Systems.mp4 (5.08 MB)
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3 Content-based Filtering.mp4 (7.02 MB)
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4 Collaborative Filtering.mp4 (3.1 MB)
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5 Recommender Systems - Business Use Cases.mp4 (9.58 MB)
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6 Module Summary.mp4 (1.38 MB)
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1 Module Overview.mp4 (1.55 MB)
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2 Understanding Memory-based Collaborative Filtering.mp4 (6.23 MB)
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3 Demo - Setting up Your Environment.mp4 (6.64 MB)
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4 Demo - Dataset Introduction and Exploratory Data Analysis.mp4 (17.94 MB)
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5 Demo - User-based Collaborative Filtering.mp4 (21.89 MB)
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6 Demo - Item-based Collaborative Filtering.mp4 (20.21 MB)
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7 Module Summary.mp4 (1.02 MB)
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1 Module Overview.mp4 (1.19 MB)
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2 Understanding Model-based Collaborative Filtering.mp4 (13.27 MB)
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3 Demo - Movie Recommendations with SVD.mp4 (13.3 MB)
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4 Demo - Book Recommendations with Deep Learning.mp4 (17.67 MB)
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5 Module Summary and Feedback.mp4 (1.43 MB)
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1 Course Overview.mp4 (2.6 MB)
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1 Building a Foundation.mp4 (9.22 MB)
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2 Building up Your Dataset.mp4 (7.3 MB)
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3 Demo - Bringing It into Practice.mp4 (29.91 MB)
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4 Finalizing Your Dataset.mp4 (606.92 KB)
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1 Detector Models, Frameworks, and Libraries.mp4 (12.41 MB)
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2 DataFormats and Computing.mp4 (6.01 MB)
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3 General Object Detection Script Setup.mp4 (6.25 MB)
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4 Training a Model - Scripted and PaaS.mp4 (23.29 MB)
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5 Evaluating a Detector.mp4 (3.19 MB)
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1 Deployment and MLOps.mp4 (14.21 MB)
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2 Drift, Retaining, and Model Store.mp4 (19.13 MB)
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3 Inferencing.mp4 (2.37 MB)
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4 Summary.mp4 (679.86 KB)
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1 Course Overview.mp4 (3.26 MB)
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1 Course and Module Summary.mp4 (3.7 MB)
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2 What Is Time Series Data.mp4 (8.48 MB)
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3 Analysing Time Series Data.mp4 (6.67 MB)
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4 Stationarity and Autocorrelation.mp4 (6.77 MB)
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5 Introduction to Anomaly Detection.mp4 (5.66 MB)
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6 Demo - Setting up Your Environment.mp4 (7.66 MB)
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7 Module Summary.mp4 (1.54 MB)
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01 Module Overview.mp4 (1.53 MB)
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02 STL Decomposition.mp4 (2.89 MB)
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03 Classification and Regression Trees (CART).mp4 (6.44 MB)
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04 Clustering-based Anomaly Detection.mp4 (5.66 MB)
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05 Anomaly Detection Using Autoencoders.mp4 (4.99 MB)
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06 Demo - Introduction to the Problem and Dataset.mp4 (5.13 MB)
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07 Demo - Exploratory Data Analysis and Data Cleaning.mp4 (29.19 MB)
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08 Demo - Data Preprocessing and Dimensionality Reduction.mp4 (18.34 MB)
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09 Demo - Building a Model for Anomaly Detection.mp4 (22.43 MB)
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10 Module Summary.mp4 (1.88 MB)
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1 Module Overview.mp4 (1.03 MB)
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2 Demo - Evaluating the Anomaly Detection Models.mp4 (15.57 MB)
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3 How to Deal with Anomalies.mp4 (2.58 MB)
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4 Module Summary and Feedback.mp4 (1.35 MB)
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1 Course Overview.mp4 (3.46 MB)
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1 Overview.mp4 (1.15 MB)
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2 Introducing Data Driven Marketing.mp4 (5.16 MB)
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3 Exploring Data Driven Trends in Marketing.mp4 (15.05 MB)
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4 Getting Started with Artificial Intelligence.mp4 (5.49 MB)
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5 Getting Acquainted with Machine Learning.mp4 (4.65 MB)
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6 Introducing Deep Learning.mp4 (5.09 MB)
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7 Understanding Deep Learning Applications in Marketin.mp4 (4.35 MB)
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8 Summary.mp4 (1.03 MB)
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1 Overview.mp4 (2.27 MB)
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2 Introducing Customer Engagement Marketing.mp4 (5.23 MB)
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3 Explaining Conversational Artificial Intelligence.mp4 (3.65 MB)
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4 Understanding the Three Stages of Conversational Artificial Int.mp4 (13.61 MB)
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5 Integrating Deep Learning in Customer Engagement.mp4 (2.92 MB)
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6 Introducing Personalized Customer Interactions.mp4 (3.68 MB)
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7 Understanding Generative Adversarial Networks.mp4 (8 MB)
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8 Utilizing Generative Adversarial Networks in Personalized Inter.mp4 (5.35 MB)
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9 Summary.mp4 (1.72 MB)
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1 Course Overview.mp4 (2.2 MB)
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1 Discussing the Importance of Neural Network in Finance.mp4 (6.05 MB)
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2 Importance of Back Propagation.mp4 (4.96 MB)
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3 Understanding CNN and RNN.mp4 (4.08 MB)
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4 Risks and Problems Associated with Finance Industry.mp4 (3.4 MB)
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5 Summary.mp4 (607.24 KB)
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1 Challenges of RNN.mp4 (3.4 MB)
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2 Overview of LSTM and GRU.mp4 (2.37 MB)
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3 Factors Impacting a Stock.mp4 (1.74 MB)
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4 Demo - Input Data of Tesla Stock.mp4 (10.3 MB)
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5 Demo - Exploratory Data Analysis.mp4 (2.97 MB)
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6 Demo - Preparing Training and Test Dataset.mp4 (3.74 MB)
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7 Summary.mp4 (627.12 KB)
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1 Parameters Impacting the Stock Price of Tesla.mp4 (3.59 MB)
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2 LSTM Advantages.mp4 (997.16 KB)
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3 Challenges for Wider Acceptance of AI in Finance.mp4 (2.62 MB)
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4 Demo - Training Stacked LSTM Model.mp4 (6.5 MB)
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5 Demo - Evaluate the Model to Predict Future Price of Tesla Stock.mp4 (5.31 MB)
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6 Summary.mp4 (440.48 KB)
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1 Course Overview.mp4 (2.93 MB)
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1 Use Case - Customer Segmentation.mp4 (8.08 MB)
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2 Use Case - Inventory Management.mp4 (4.82 MB)
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3 Use Case - Product Image Classification.mp4 (4.03 MB)
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4 Use Case - Price Optimization.mp4 (4.71 MB)
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5 Data Collection.mp4 (6.39 MB)
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6 Current Trends.mp4 (5.56 MB)
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1 Framing the Problem.mp4 (6.49 MB)
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2 Implementation.mp4 (4.87 MB)
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3 Results.mp4 (4.75 MB)
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4 Tips for Success.mp4 (3.13 MB)
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1 Framing the Problem.mp4 (3.83 MB)
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2 Implementation.mp4 (13.23 MB)
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3 Results.mp4 (9.05 MB)
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4 Tips for Success.mp4 (3.36 MB)
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1 Summary.mp4 (6.32 MB)
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1 Course Overview.mp4 (4.12 MB)
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1 Course and Module Introduction.mp4 (5.22 MB)
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2 What Are We Trying to Solve.mp4 (9.94 MB)
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3 Demo - Setting up Your Environment.mp4 (6.57 MB)
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4 Demo - Organizing the Dataset.mp4 (11.15 MB)
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5 Demo - Exploring the Dataset.mp4 (6.66 MB)
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6 Demo - Preprocessing and Preparing the Dataset.mp4 (10.28 MB)
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7 Summary and Up Next.mp4 (1.47 MB)
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01 Module Introduction.mp4 (1.4 MB)
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02 What Are Convolutional Neural Networks.mp4 (3.97 MB)
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03 CNN - Convolutions.mp4 (6.79 MB)
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04 CNN - Activation.mp4 (7.65 MB)
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05 CNN - Pooling.mp4 (1.97 MB)
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06 CNN - Classification.mp4 (1.39 MB)
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07 Demo - Creating the CNN Architecture.mp4 (10.79 MB)
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08 Demo - Training the Model.mp4 (4.38 MB)
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09 Demo - Performance Metrics – How Well Did Your Model Do.mp4 (6.72 MB)
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10 Summary and Up Next.mp4 (1.76 MB)
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01 Module Introduction.mp4 (2.05 MB)
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02 Better Performance – When and How.mp4 (2.76 MB)
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03 Procuring Additional Training Data – Image Augmentation.mp4 (7.48 MB)
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04 Hyperparameter Tuning.mp4 (4.39 MB)
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05 Overfitting and Underfitting.mp4 (5.44 MB)
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06 Demo - Image Augmentation and Hyperparameter Tuning.mp4 (17.16 MB)
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07 What Is Transfer Learning.mp4 (6.67 MB)
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08 Transfer Learning – When and How.mp4 (5.76 MB)
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09 Demo - Improving Performance through Transfer Learning.mp4 (7.29 MB)
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10 Summary.mp4 (1.75 MB)
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1 Overview.mp4 (1.63 MB)
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2 Explore Enron Email Dataset.mp4 (5.65 MB)
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3 Extract Plaintext Messages from Raw Email Data.mp4 (8.63 MB)
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4 Clean the Email Dataset.mp4 (11.95 MB)
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5 Functions to Preprocess the Dataset.mp4 (15.67 MB)
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6 Preprocess the Email Dataset.mp4 (10.34 MB)
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7 Summary.mp4 (1.04 MB)
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1 Overview.mp4 (1.62 MB)
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2 Network Architecture for Text Generation.mp4 (8.1 MB)
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3 Tokenization, Vocabulary, and N-grams.mp4 (12.9 MB)
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4 Handle Variable Sentence Lengths.mp4 (8.26 MB)
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5 Predictors and Labels for Training.mp4 (5.81 MB)
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6 Build and Train the Model.mp4 (9.7 MB)
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7 Generate Auto-complete Suggestions.mp4 (9.78 MB)
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8 Summary.mp4 (1.89 MB)
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1 Course Overview.mp4 (2.97 MB)
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1 Overview.mp4 (1.8 MB)
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2 Introduction to Neural Networks.mp4 (9.77 MB)
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3 Natural Language Text as Sequential Data.mp4 (5.12 MB)
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4 Recurrent Neural Networks (RNNs).mp4 (11.72 MB)
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5 Long Short-term Memory Networks (LSTMs).mp4 (10.55 MB)
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6 Networks Architectures Using LSTMs.mp4 (8.7 MB)
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7 Natural Language Generation Using LSTMs.mp4 (5.76 MB)
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8 Summary.mp4 (1.7 MB)
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1 Course Overview.mp4 (3.13 MB)
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1 Overview.mp4 (6.5 MB)
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2 What Is Image Captioning and Why Is It Important.mp4 (5.96 MB)
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3 Introducing the Business Case Study for Image-captioning.mp4 (3.3 MB)
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4 Proposed Solutions for Image Captioning Case Study.mp4 (9.61 MB)
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5 Summary.mp4 (1.31 MB)
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1 Module and Project Overview.mp4 (12.67 MB)
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2 Demo - Load and Explore the Dataset.mp4 (25.04 MB)
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3 Demo - Pre-processing the Images Data.mp4 (21.61 MB)
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4 Demo - Pre-processing the Captions Data.mp4 (19.61 MB)
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5 Demo - Prepare Training Data Using Pre-processed Data.mp4 (11.68 MB)
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6 Summary.mp4 (1.09 MB)
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1 Overview.mp4 (1.48 MB)
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2 Demo - Build the Attention Model for Image-captioning Using TensorFlow.mp4 (13.05 MB)
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3 Demo - Implement CNN Encoder in TensorFlow.mp4 (3.68 MB)
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4 Demo - Implement RNN Decoder with Attention & Sentence Generator.mp4 (6.78 MB)
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5 Demo - Define the Loss Function and Model Checkpoints.mp4 (6.77 MB)
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6 Demo - Perform Model Training.mp4 (9.92 MB)
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7 Demo - Making Predictions out of the Trained Model.mp4 (4.53 MB)
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8 Summary.mp4 (1.02 MB)
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1 Overview.mp4 (1.36 MB)
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2 Meshed Memory Transformer for Image Captioning.mp4 (6.83 MB)
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3 Evaluation Metrics for Image Captioning.mp4 (17 MB)
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4 Bottom-up and Top-down Attention for Image Captioning.mp4 (4.09 MB)
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5 Summary.mp4 (4.18 MB)
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1 Course Overview.mp4 (2.8 MB)
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1 Overview.mp4 (1.65 MB)
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2 Introduction to Deep Neural Networks.mp4 (8.07 MB)
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3 Training Deep Neural Networks.mp4 (5.76 MB)
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4 Natural Language Text as Sequential Data.mp4 (4.92 MB)
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5 Recurrent Neural Networks (RNNs).mp4 (8.34 MB)
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6 Neural Network Architectures Using RNNs.mp4 (6.99 MB)
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7 Text Classification Using RNNs.mp4 (4.97 MB)
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8 Limitations of Recurrent Neural Networks.mp4 (2.66 MB)
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9 Summary.mp4 (1.87 MB)
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1 Overview.mp4 (1.85 MB)
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2 Explore the Spambase Dataset.mp4 (5.76 MB)
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3 Extract Predictors and Labels for Training.mp4 (5.52 MB)
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4 Perform Tokenization and Create Vocabulary.mp4 (9.54 MB)
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5 Padding Variable Length Sequences.mp4 (8.24 MB)
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6 Create and Train the Model.mp4 (12.54 MB)
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7 Classify Emails Using the Trained Model.mp4 (4.36 MB)
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8 Summary.mp4 (1.32 MB)
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01 Overview.mp4 (1.68 MB)
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02 Explore the Amazon Product Review Dataset.mp4 (12.94 MB)
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03 Extract Reviews and Sentiments.mp4 (8.38 MB)
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04 Convert Sentiments to Vectors.mp4 (5.18 MB)
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05 Cleaning of the Review Texts.mp4 (18.18 MB)
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06 Perform Tokenization and Create Vocabulary.mp4 (4.58 MB)
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07 Padding Variable Length Sequences.mp4 (5.5 MB)
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08 Create Model and Training.mp4 (9.92 MB)
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09 Predict Sentiments Using the Trained Model.mp4 (4.85 MB)
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10 Summary.mp4 (1.81 MB)
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1 Course Overview.mp4 (2.76 MB)
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1 Why Should We Process Text.mp4 (5.32 MB)
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2 Demo - Introducing Globomantics Case Study.mp4 (1.51 MB)
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3 Getting the Best out of This Course.mp4 (3.82 MB)
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4 Version Check.mp4 (3.2 MB)
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5 Outline of the Course.mp4 (2.08 MB)
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1 How to Represent Words.mp4 (4.8 MB)
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2 First Embedding - One Hot Encoding.mp4 (3.87 MB)
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3 Demo - Using OHE.mp4 (31.95 MB)
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4 Demo - Analyzing Sentiment with OHE.mp4 (22.41 MB)
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5 Training Embeddings with Networks - CBOW and Skip-gram.mp4 (7.9 MB)
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6 Demo - Training a CBOW Embedding.mp4 (40.39 MB)
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7 Demo - Reanalyze Sentiment with a Network-based Embedding.mp4 (26.42 MB)
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8 What Comes Next.mp4 (3.18 MB)
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1 Why Would We Fine Tune Existing Models.mp4 (3.59 MB)
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2 Demo - Fine Tuning Glove and FastText.mp4 (64.48 MB)
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3 Demo - Making Word Clusters.mp4 (20.4 MB)
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4 Demo - Debiase Word Embeddings.mp4 (38.47 MB)
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5 Key Takeaways and Tips.mp4 (1.65 MB)
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6 Where to Go Next.mp4 (4.04 MB)
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