Pluralsight Path. Deep Learning Literacy. Practical Application (2022)

C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/exercise.7z

C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/2. Demo - Fine Tuning Glove and FastText.mp4

C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/6. Demo - Training a CBOW Embedding.mp4

C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/4. Demo - Debiase Word Embeddings.mp4

C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/3. Demo - Using OHE.mp4

C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/2. Preparing Data for Model Training/3. Demo - Bringing It into Practice.mp4

C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/07. Demo - Exploratory Data Analysis and Data Cleaning.mp4

C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/7. Demo - Reanalyze Sentiment with a Network-based Embedding.mp4

B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/exercise.7z

B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/2. Demo - Load and Explore the Dataset.mp4

C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/4. Training a Model - Scripted and PaaS.mp4

C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/09. Demo - Building a Model for Anomaly Detection.mp4

C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/3. Training Word Representations/4. Demo - Analyzing Sentiment with OHE.mp4

C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/5. Demo - User-based Collaborative Filtering.mp4

B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/3. Demo - Pre-processing the Images Data.mp4

C1. Implement Natural Language Processing for Word Embedding (Axel Sirota, 2022)/4. Fine-tuning Word Representations/3. Demo - Making Word Clusters.mp4

C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/6. Demo - Item-based Collaborative Filtering.mp4

B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/4. Demo - Pre-processing the Captions Data.mp4

C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/2. Drift, Retaining, and Model Store.mp4

C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/3. Building a Model to Automate Anomaly Detection/08. Demo - Data Preprocessing and Dimensionality Reduction.mp4

C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/3. Memory-based Collaborative Filtering/4. Demo - Dataset Introduction and Exploratory Data Analysis.mp4

C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/4. Demo - Book Recommendations with Deep Learning.mp4

B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/4. Improving Performance of the Convolutional Neural Network/06. Demo - Image Augmentation and Hyperparameter Tuning.mp4

B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/5. Evaluating Deep Learning Models for Image Captioning/3. Evaluation Metrics for Image Captioning.mp4

B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/5. Functions to Preprocess the Dataset.mp4

C4. Build a Model for Anomaly Detection in Time Series Data (Pratheerth Padman, 2022)/4. Model Evaluation and Dealing with Anomalies/2. Demo - Evaluating the Anomaly Detection Models.mp4

A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/2. Introducing Deep Learning as Part of Artificial Intelligence and Its Usage in Digital Marketing/3. Exploring Data Driven Trends in Marketing.mp4

C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/4. Deployment/1. Deployment and MLOps.mp4

A2. Deep Learning Application for Marketing (Netta Tzin, 2022)/3. Exploring Deep Learning Applications in Marketing through Various Business Use-cases/4. Understanding the Three Stages of Conversational Artificial Intelligence.mp4

C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/3. Demo - Movie Recommendations with SVD.mp4

C2. Build a Rating Recommendation Engine with Collaborative Filtering (Pratheerth Padman, 2022)/4. Model-based Collaborative Filtering/2. Understanding Model-based Collaborative Filtering.mp4

A4. Deep Learning Application for Retail (Trent McMillan, 2022)/4. Case Study - Churn Prediction/2. Implementation.mp4

B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/exercise.7z

B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/2. Demo - Build the Attention Model for Image-captioning Using TensorFlow.mp4

B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/3. Tokenization, Vocabulary, and N-grams.mp4

B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/1. Module and Project Overview.mp4

C3. Build an Object Detection Model with Python (Gabrielle Davelaar, 2022)/3. Training/1. Detector Models, Frameworks, and Libraries.mp4

B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/4. Clean the Email Dataset.mp4

B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/4. Recurrent Neural Networks (RNNs).mp4

B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/3. Preparing Data for Image Captioning Models/5. Demo - Prepare Training Data Using Pre-processed Data.mp4

A4. Deep Learning Application for Retail (Trent McMillan, 2022)/exercise.7z

B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/4. Demo - Organizing the Dataset.mp4

B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/3. Training a Convolutional Neural Network to Classify Images/07. Demo - Creating the CNN Architecture.mp4

B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/2. Long Short Term Memory Networks (LSTM)/5. Long Short-term Memory Networks (LSTMs).mp4

B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/3. Data Preparation for Assisted Smart Writing/6. Preprocess the Email Dataset.mp4

A3. Deep Learning Application for Finance (Jaimin M, 2022)/3. Analyzing the Importance of Deep Learning Algorithm to Predict a Stock Price/4. Demo - Input Data of Tesla Stock.mp4

B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/6. Demo - Preprocessing and Preparing the Dataset.mp4

B1. Implement Image Recognition with a Convolutional Neural Network (Pratheerth Padman, 2022)/2. Exploring and Preparing a Dataset for Image Recognition/2. What Are We Trying to Solve.mp4

B3. Implement Image Captioning with Recurrent Neural Networks (Abdul Rehman Yousaf, 2022)/4. Building the Model for Image Captioning Using Tensorflow/6. Demo - Perform Model Training.mp4

B2. Implement Text Auto Completion with LSTM (Biswanath Halder, 2022)/4. Implementation of Auto-completion for Assisted Smart Writing/7. Generate Auto-complete Suggestions.mp4