Udemy - Machine Learning, Data Science and Generative AI with Python (1.2025)

磁力链接/BT种子名称

Udemy - Machine Learning, Data Science and Generative AI with Python (1.2025)

磁力链接/BT种子简介

种子哈希：9b004af67bc1aadf759b350dccf81fa0692e5ede
文件大小： 7.79G
已经下载：797次
下载速度：极快
收录时间：2025-06-23
最近下载：2025-10-12

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磁力链接

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API Integration

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文件列表

  • 13. The OpenAI API (Developing with GPT and ChatGPT)/7. The New OpenAI Fine-Tuning API Fine-Tuning GPT-3.5 to simulate Commander Data!.mp4 334.5 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/4. Activity Evaluating our RAG-based Cdr. Data using RAGAS and langchain.mp4 283.9 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/8. Activity Simulating Cdr. Data with Advanced RAG and langchain.mp4 277.3 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/10. Activity Building a Cdr. Data chatbot with LLM Agents, web search & math tools.mp4 276.6 MB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/6. Demo Fine-Tuning OpenAI's Davinci Model to simulate Data from Star Trek.mp4 174.6 MB
  • 11. Generative Models/2. Variational Auto-Encoders (VAE) - Hands-on with Fashion MNIST.mp4 156.1 MB
  • 08. Apache Spark Machine Learning on Big Data/3. Activity Installing Spark.mp4 148.2 MB
  • 08. Apache Spark Machine Learning on Big Data/7. Introduction to Decision Trees in Spark.mp4 140.5 MB
  • 11. Generative Models/5. Generative Adversarial Networks (GAN's) - Hands-on with Fashion MNIST.mp4 132.2 MB
  • 06. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.mp4 131.3 MB
  • 05. Recommender Systems/5. Activity Making Movie Recommendations with Item-Based Collaborative Filtering.mp4 130.1 MB
  • 10. Deep Learning and Neural Networks/17. The Ethics of Deep Learning.mp4 126.4 MB
  • 08. Apache Spark Machine Learning on Big Data/8. Activity K-Means Clustering in Spark.mp4 121.8 MB
  • 10. Deep Learning and Neural Networks/14. Activity Transfer Learning.mp4 116.4 MB
  • 10. Deep Learning and Neural Networks/6. Activity Using Tensorflow, Part 1.mp4 112.9 MB
  • 02. Statistics and Probability Refresher, and Python Practice/4. Activity Variation and Standard Deviation.mp4 108.4 MB
  • 01. Getting Started/5. Activity WINDOWS Installing and Using Anaconda & Course Materials.mp4 106.9 MB
  • 02. Statistics and Probability Refresher, and Python Practice/9. Activity Advanced Visualization with Seaborn.mp4 100.8 MB
  • 01. Getting Started/6. Activity MAC Installing and Using Anaconda & Course Materials.mp4 100.4 MB
  • 10. Deep Learning and Neural Networks/7. Activity Using Tensorflow, Part 2.mp4 99.7 MB
  • 03. Predictive Models/3. Activity Multiple Regression, and Predicting Car Prices.mp4 98.7 MB
  • 02. Statistics and Probability Refresher, and Python Practice/11. Exercise Conditional Probability.mp4 98.5 MB
  • 03. Predictive Models/1. Activity Linear Regression.mp4 97.5 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/1. Retrieval Augmented Generation (RAG) How it works, with some examples.mp4 97.4 MB
  • 09. Experimental Design ML in the Real World/6. AB Test Gotchas.mp4 96.2 MB
  • 02. Statistics and Probability Refresher, and Python Practice/8. Activity A Crash Course in matplotlib.mp4 93.0 MB
  • 11. Generative Models/4. Generative Adversarial Networks (GAN's) - Playing with some demos.mp4 92.9 MB
  • 06. More Data Mining and Machine Learning Techniques/2. Activity Using KNN to predict a rating for a movie.mp4 89.7 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/11. Activity Fine Tuning GPT with the IMDb dataset.mp4 89.3 MB
  • 08. Apache Spark Machine Learning on Big Data/10. Activity Searching Wikipedia with Spark.mp4 88.1 MB
  • 05. Recommender Systems/3. Activity Finding Movie Similarities using Cosine Similarity.mp4 86.7 MB
  • 05. Recommender Systems/1. User-Based Collaborative Filtering.mp4 85.7 MB
  • 04. Machine Learning with Python/11. Decision Trees Concepts.mp4 85.5 MB
  • 04. Machine Learning with Python/4. Activity Implementing a Spam Classifier with Naive Bayes.mp4 85.3 MB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/2. Activity Using Tools and Functions in the OpenAI Chat Completion API.mp4 85.1 MB
  • 04. Machine Learning with Python/14. Activity XGBoost.mp4 83.1 MB
  • 10. Deep Learning and Neural Networks/13. Activity Using a RNN for sentiment analysis.mp4 77.1 MB
  • 02. Statistics and Probability Refresher, and Python Practice/1. Types of Data (Numerical, Categorical, Ordinal).mp4 76.7 MB
  • 07. Dealing with Real-World Data/3. Data Cleaning and Normalization.mp4 76.6 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/2. Demo Using Retrieval Augmented Generation (RAG) to simulate Data from Star Trek.mp4 76.0 MB
  • 10. Deep Learning and Neural Networks/8. Activity Introducing Keras.mp4 75.5 MB
  • 10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.mp4 73.8 MB
  • 02. Statistics and Probability Refresher, and Python Practice/10. Activity Covariance and Correlation.mp4 72.9 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/10. Activity Using small and large GPT models within Google CoLab and HuggingFace.mp4 72.4 MB
  • 10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.mp4 72.2 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/7. Activity Tokenization with Google CoLab and HuggingFace.mp4 71.0 MB
  • 10. Deep Learning and Neural Networks/9. Activity Using Keras to Predict Political Affiliations.mp4 70.1 MB
  • 06. More Data Mining and Machine Learning Techniques/4. Activity PCA Example with the Iris data set.mp4 69.0 MB
  • 08. Apache Spark Machine Learning on Big Data/9. TF IDF.mp4 68.9 MB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/1. Activity The OpenAI Chat Completions API.mp4 68.6 MB
  • 08. Apache Spark Machine Learning on Big Data/11. Activity Using the Spark DataFrame API for MLLib.mp4 68.3 MB
  • 15. Final Project/2. Final project review.mp4 67.6 MB
  • 06. More Data Mining and Machine Learning Techniques/7. Activity Reinforcement Learning & Q-Learning with Gym.mp4 65.8 MB
  • 03. Predictive Models/2. Activity Polynomial Regression.mp4 63.5 MB
  • 01. Getting Started/7. Activity LINUX Installing and Using Anaconda & Course Materials.mp4 63.1 MB
  • 10. Deep Learning and Neural Networks/10. Convolutional Neural Networks (CNN's).mp4 61.6 MB
  • 06. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.mp4 61.6 MB
  • 04. Machine Learning with Python/12. Activity Decision Trees Predicting Hiring Decisions.mp4 60.6 MB
  • 07. Dealing with Real-World Data/2. Activity K-Fold Cross-Validation to avoid overfitting.mp4 59.7 MB
  • 04. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.mp4 59.4 MB
  • 02. Statistics and Probability Refresher, and Python Practice/13. Bayes' Theorem.mp4 58.8 MB
  • 05. Recommender Systems/4. Activity Improving the Results of Movie Similarities.mp4 58.8 MB
  • 10. Deep Learning and Neural Networks/3. Activity Deep Learning in the Tensorflow Playground.mp4 58.4 MB
  • 10. Deep Learning and Neural Networks/11. Activity Using CNN's for handwriting recognition.mp4 55.4 MB
  • 15. Final Project/1. Your final project assignment Mammogram Classification.mp4 54.1 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/12. From GPT to ChatGPT Deep Reinforcement Learning, Proximal Policy Gradients.mp4 53.6 MB
  • 09. Experimental Design ML in the Real World/4. Activity Hands-on With T-Tests.mp4 50.1 MB
  • 10. Deep Learning and Neural Networks/5. Introducing Tensorflow.mp4 48.9 MB
  • 02. Statistics and Probability Refresher, and Python Practice/3. Activity Using mean, median, and mode in Python.mp4 46.7 MB
  • 01. Getting Started/12. Introducing the Pandas Library Optional.mp4 46.3 MB
  • 11. Generative Models/1. Variational Auto-Encoders (VAE's) - how they work.mp4 45.0 MB
  • 07. Dealing with Real-World Data/10. Binning, Transforming, Encoding, Scaling, and Shuffling.mp4 44.8 MB
  • 02. Statistics and Probability Refresher, and Python Practice/7. Activity Percentiles and Moments.mp4 44.6 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/2. Self-Attention, Masked Self-Attention, and Multi-Headed Self Attention in depth.mp4 43.5 MB
  • 04. Machine Learning with Python/16. Activity Using SVM to cluster people using scikit-learn.mp4 40.4 MB
  • 06. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction Principal Component Analysis (PCA).mp4 40.0 MB
  • 04. Machine Learning with Python/13. Ensemble Learning.mp4 38.8 MB
  • 16. You made it!/1. More to Explore.mp4 35.6 MB
  • 10. Deep Learning and Neural Networks/12. Recurrent Neural Networks (RNN's).mp4 34.4 MB
  • 09. Experimental Design ML in the Real World/2. AB Testing Concepts.mp4 33.6 MB
  • 07. Dealing with Real-World Data/4. Activity Cleaning web log data.mp4 32.5 MB
  • 10. Deep Learning and Neural Networks/4. Deep Learning Details.mp4 32.4 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/9. Activity Masked, Multi-Headed Self Attention with BERT, BERTViz, and exBERT.mp4 31.9 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/4. How GPT Works, Part 1 The GPT Transformer Architecture.mp4 31.7 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/5. Advanced RAG Pre-Retrieval chunking semantic chunking data extraction.mp4 30.9 MB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/4. Activity The Embeddings API in OpenAI Finding similarities between words.mp4 30.4 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/13. From GPT to ChatGPT Reinforcement Learning from Human Feedback and Moderation.mp4 29.9 MB
  • 02. Statistics and Probability Refresher, and Python Practice/6. Common Data Distributions (Normal, Binomial, Poisson, etc).mp4 29.6 MB
  • 05. Recommender Systems/6. Exercise Improve the recommender's results.mp4 29.4 MB
  • 03. Predictive Models/4. Multi-Level Models.mp4 28.5 MB
  • 07. Dealing with Real-World Data/6. Activity Detecting outliers.mp4 28.5 MB
  • 01. Getting Started/8. Python Basics, Part 1 Optional.mp4 28.2 MB
  • 04. Machine Learning with Python/5. K-Means Clustering.mp4 27.3 MB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/3. Activity The Images (DALL-E) API in OpenAI.mp4 27.0 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/3. RAG Metrics The RAG Triad, relevancy, recall, precision, accuracy, and more.mp4 26.3 MB
  • 08. Apache Spark Machine Learning on Big Data/4. Spark Introduction.mp4 26.2 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/9. LLM Agents and Swarms of Agents.mp4 25.9 MB
  • 07. Dealing with Real-World Data/1. BiasVariance Tradeoff.mp4 24.8 MB
  • 05. Recommender Systems/2. Item-Based Collaborative Filtering.mp4 24.3 MB
  • 08. Apache Spark Machine Learning on Big Data/5. Spark and the Resilient Distributed Dataset (RDD).mp4 23.4 MB
  • 04. Machine Learning with Python/6. Activity Clustering people based on income and age.mp4 23.1 MB
  • 04. Machine Learning with Python/2. Activity Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 22.7 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/7. Advanced RAG Prompt Compression, and More Tuning Opportunities.mp4 22.5 MB
  • 01. Getting Started/9. Activity Python Basics, Part 2 Optional.mp4 21.6 MB
  • 11. Generative Models/6. Learning More about Deep Learning.mp4 21.2 MB
  • 10. Deep Learning and Neural Networks/16. Deep Learning Regularization with Dropout and Early Stopping.mp4 20.8 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/1. The Transformer Architecture (encoders, decoders, and self-attention.).mp4 20.7 MB
  • 01. Getting Started/1. Introduction.mp4 19.7 MB
  • 07. Dealing with Real-World Data/8. Imputation Techniques for Missing Data.mp4 19.1 MB
  • 07. Dealing with Real-World Data/9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4 18.3 MB
  • 01. Getting Started/2. Udemy 101 Getting the Most From This Course.mp4 18.2 MB
  • 09. Experimental Design ML in the Real World/1. Deploying Models to Real-Time Systems.mp4 18.1 MB
  • 04. Machine Learning with Python/15. Support Vector Machines (SVM) Overview.mp4 17.1 MB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/8. Activity The OpenAI Moderation API.mp4 17.0 MB
  • 02. Statistics and Probability Refresher, and Python Practice/2. Mean, Median, Mode.mp4 16.7 MB
  • 11. Generative Models/3. Generative Adversarial Networks (GAN's) - How they work.mp4 16.0 MB
  • 02. Statistics and Probability Refresher, and Python Practice/12. Exercise Solution Conditional Probability of Purchase by Age.mp4 15.7 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/5. How GPT Works, Part 2 Tokenization, Positional Encoding, Embedding.mp4 15.5 MB
  • 08. Apache Spark Machine Learning on Big Data/6. Introducing MLLib.mp4 15.4 MB
  • 07. Dealing with Real-World Data/7. Feature Engineering and the Curse of Dimensionality.mp4 15.3 MB
  • 09. Experimental Design ML in the Real World/3. T-Tests and P-Values.mp4 14.8 MB
  • 06. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.mp4 14.7 MB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/9. Activity The OpenAI Audio API (speech to text).mp4 13.6 MB
  • 04. Machine Learning with Python/7. Measuring Entropy.mp4 12.7 MB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/5. The Legacy Fine-Tuning API for GPT Models in OpenAI.mp4 12.2 MB
  • 06. More Data Mining and Machine Learning Techniques/9. Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4 12.2 MB
  • 07. Dealing with Real-World Data/5. Normalizing numerical data.mp4 10.8 MB
  • 04. Machine Learning with Python/3. Bayesian Methods Concepts.mp4 10.3 MB
  • 09. Experimental Design ML in the Real World/5. Determining How Long to Run an Experiment.mp4 10.2 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/3. Applications of Transformers (GPT).mp4 10.0 MB
  • 04. Machine Learning with Python/9. Activity MAC Installing Graphviz.mp4 9.5 MB
  • 10. Deep Learning and Neural Networks/15. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 8.9 MB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/6. Advanced RAG Query Rewriting.mp4 8.5 MB
  • 06. More Data Mining and Machine Learning Techniques/8. Understanding a Confusion Matrix.mp4 7.7 MB
  • 02. Statistics and Probability Refresher, and Python Practice/5. Probability Density Function Probability Mass Function.mp4 7.3 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/7. Transformers_MLCourse.ipynb 7.0 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/8. Activity Positional Encoding.mp4 6.8 MB
  • 01. Getting Started/11. Activity Python Basics, Part 4 Optional.mp4 6.0 MB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/6. Fine Tuning Transfer Learning with Transformers.mp4 5.3 MB
  • 11. Generative Models/5. GAN_on_Fashion_MNIST.ipynb 3.9 MB
  • 04. Machine Learning with Python/10. Activity LINUX Installing Graphviz.mp4 2.6 MB
  • 01. Getting Started/10. Activity Python Basics, Part 3 Optional.mp4 2.6 MB
  • 11. Generative Models/2. VariationalAutoEncoders.ipynb 1.4 MB
  • 04. Machine Learning with Python/8. Activity WINDOWS Installing Graphviz.mp4 972.1 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/8. Data_Advanced_RAG.ipynb 781.9 kB
  • 16. You made it!/3. 2019-04-08_18-15-28-b861b8ffb2406e3f70aad5871e4e91ff.png 135.8 kB
  • 16. You made it!/3. 2019-04-08_17-55-57-bcf2d7bf9cef514f135511b184f77e48.png 135.6 kB
  • 16. You made it!/3. 2019-04-08_18-17-01-1a5b2a5d579cfb42118eaf525e7a7b83.png 130.7 kB
  • 16. You made it!/3. 2019-04-08_18-17-59-492c9dc76de5ed12f532ead3e609f148.png 129.8 kB
  • 16. You made it!/3. 2019-04-08_18-01-48-cf6d9b7536a1e4a75438299681428036.png 124.7 kB
  • 16. You made it!/3. 2019-04-08_18-03-42-4930e7b3a27d368a568d97fd8c959359.png 124.3 kB
  • 16. You made it!/3. 2019-04-08_18-19-48-5bc03a831100a771082c4245e271a4b0.png 117.4 kB
  • 16. You made it!/3. 2019-04-08_18-04-33-85f2594b9a584964a59514617b27f95b.png 114.3 kB
  • 16. You made it!/3. 2019-05-14_17-14-40-e1d4913408ac3d0f1eaad1a80705cf5b.png 104.7 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/2. Data_RAG.ipynb 102.8 kB
  • 16. You made it!/3. 2019-04-08_18-20-39-de5ee610f1e6e8e483229fd1c9d7e998.png 95.1 kB
  • 16. You made it!/3. 2024-07-26_12-45-38-32f4df5ac9105153f0fd5c7fdab93d89.png 94.6 kB
  • 16. You made it!/3. 2022-07-23_11-27-36-c40b770315b5187e58bca3c2542ee3b4.png 85.5 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/10. Data_Agent.ipynb 85.3 kB
  • 16. You made it!/3. 2024-08-19_12-50-25-5160f601d41d2a72d06a9c0d700cad51.png 85.1 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/4. Data_RAG_Metrics.ipynb 73.7 kB
  • 16. You made it!/3. 2021-10-16_12-16-09-e3dd0e05ba917baf745a42fc35a0cbb2.jpg 72.3 kB
  • 16. You made it!/3. 2022-04-18_13-12-40-afb201ce74196d83694608d7fc39a43e.png 61.5 kB
  • 16. You made it!/3. 2019-04-08_18-21-33-2ee7f2d5dff7cccfd9f4103899aa6cc0.png 61.0 kB
  • 16. You made it!/3. 2019-04-08_19-24-33-63d41c7c27f7ed6e9ca0e1072e6c2751.jpg 46.6 kB
  • 11. Generative Models/2. Variational Auto-Encoders (VAE) - Hands-on with Fashion MNIST.vtt 46.4 kB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/7. The New OpenAI Fine-Tuning API Fine-Tuning GPT-3.5 to simulate Commander Data!.vtt 38.8 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/2. Demo Using Retrieval Augmented Generation (RAG) to simulate Data from Star Trek.vtt 34.3 kB
  • 16. You made it!/3. 2024-08-06_13-32-36-7f6c6c13c6b331d2282e71ed3e362b48.jpg 32.6 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/4. Activity Evaluating our RAG-based Cdr. Data using RAGAS and langchain.vtt 32.1 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/1. Retrieval Augmented Generation (RAG) How it works, with some examples.vtt 31.6 kB
  • 02. Statistics and Probability Refresher, and Python Practice/9. Activity Advanced Visualization with Seaborn.vtt 30.3 kB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/6. Demo Fine-Tuning OpenAI's Davinci Model to simulate Data from Star Trek.vtt 30.1 kB
  • 03. Predictive Models/3. Activity Multiple Regression, and Predicting Car Prices.vtt 29.1 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/10. Activity Building a Cdr. Data chatbot with LLM Agents, web search & math tools.vtt 29.0 kB
  • 02. Statistics and Probability Refresher, and Python Practice/11. Exercise Conditional Probability.vtt 28.9 kB
  • 04. Machine Learning with Python/14. Activity XGBoost.vtt 28.7 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/8. Activity Simulating Cdr. Data with Advanced RAG and langchain.vtt 28.3 kB
  • 08. Apache Spark Machine Learning on Big Data/7. Introduction to Decision Trees in Spark.vtt 28.2 kB
  • 11. Generative Models/5. Generative Adversarial Networks (GAN's) - Hands-on with Fashion MNIST.vtt 27.5 kB
  • 10. Deep Learning and Neural Networks/8. Activity Introducing Keras.vtt 24.3 kB
  • 16. You made it!/3. 2019-10-23_18-48-57-9fb797c585d7195417eca364a27b07c9.jpg 24.3 kB
  • 10. Deep Learning and Neural Networks/6. Activity Using Tensorflow, Part 1.vtt 23.5 kB
  • 02. Statistics and Probability Refresher, and Python Practice/7. Activity Percentiles and Moments.vtt 22.5 kB
  • 06. More Data Mining and Machine Learning Techniques/7. Activity Reinforcement Learning & Q-Learning with Gym.vtt 22.5 kB
  • 10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.vtt 22.2 kB
  • 10. Deep Learning and Neural Networks/5. Introducing Tensorflow.vtt 22.2 kB
  • 10. Deep Learning and Neural Networks/9. Activity Using Keras to Predict Political Affiliations.vtt 21.5 kB
  • 06. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.vtt 21.5 kB
  • 10. Deep Learning and Neural Networks/14. Activity Transfer Learning.vtt 21.4 kB
  • 10. Deep Learning and Neural Networks/10. Convolutional Neural Networks (CNN's).vtt 21.3 kB
  • 10. Deep Learning and Neural Networks/7. Activity Using Tensorflow, Part 2.vtt 21.1 kB
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/1. Activity The OpenAI Chat Completions API.vtt 21.1 kB
  • 10. Deep Learning and Neural Networks/17. The Ethics of Deep Learning.vtt 21.1 kB
  • 10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.vtt 20.5 kB
  • 06. More Data Mining and Machine Learning Techniques/2. Activity Using KNN to predict a rating for a movie.vtt 20.5 kB
  • 08. Apache Spark Machine Learning on Big Data/5. Spark and the Resilient Distributed Dataset (RDD).vtt 20.5 kB
  • 10. Deep Learning and Neural Networks/3. Activity Deep Learning in the Tensorflow Playground.vtt 20.3 kB
  • 02. Statistics and Probability Refresher, and Python Practice/10. Activity Covariance and Correlation.vtt 20.1 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/3. RAG Metrics The RAG Triad, relevancy, recall, precision, accuracy, and more.vtt 20.1 kB
  • 03. Predictive Models/1. Activity Linear Regression.vtt 20.0 kB
  • 10. Deep Learning and Neural Networks/12. Recurrent Neural Networks (RNN's).vtt 19.6 kB
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  • 05. Recommender Systems/3. Activity Finding Movie Similarities using Cosine Similarity.vtt 15.3 kB
  • 01. Getting Started/7. Activity LINUX Installing and Using Anaconda & Course Materials.vtt 15.2 kB
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  • 05. Recommender Systems/1. User-Based Collaborative Filtering.vtt 14.8 kB
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  • 04. Machine Learning with Python/5. K-Means Clustering.vtt 13.3 kB
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  • 08. Apache Spark Machine Learning on Big Data/11. Activity Using the Spark DataFrame API for MLLib.vtt 13.2 kB
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  • 02. Statistics and Probability Refresher, and Python Practice/1. Types of Data (Numerical, Categorical, Ordinal).vtt 12.3 kB
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  • 13. The OpenAI API (Developing with GPT and ChatGPT)/4. Activity The Embeddings API in OpenAI Finding similarities between words.vtt 11.4 kB
  • 08. Apache Spark Machine Learning on Big Data/9. TF IDF.vtt 11.3 kB
  • 16. You made it!/3. Bonus Lecture.html 11.3 kB
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  • 09. Experimental Design ML in the Real World/4. Activity Hands-on With T-Tests.vtt 10.6 kB
  • 09. Experimental Design ML in the Real World/3. T-Tests and P-Values.vtt 10.5 kB
  • 05. Recommender Systems/6. Exercise Improve the recommender's results.vtt 10.4 kB
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  • 07. Dealing with Real-World Data/9. Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.vtt 10.1 kB
  • 14. Retrieval Augmented Generation (RAG,) Advanced RAG, and LLM Agents/9. LLM Agents and Swarms of Agents.vtt 10.0 kB
  • 06. More Data Mining and Machine Learning Techniques/8. Understanding a Confusion Matrix.vtt 9.9 kB
  • 06. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction Principal Component Analysis (PCA).vtt 9.9 kB
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  • 13. The OpenAI API (Developing with GPT and ChatGPT)/5. The Legacy Fine-Tuning API for GPT Models in OpenAI.vtt 9.8 kB
  • 04. Machine Learning with Python/6. Activity Clustering people based on income and age.vtt 9.4 kB
  • 12. Generative AI GPT, ChatGPT, Transformers, Self Attention Based Neural Networks/10. Activity Using small and large GPT models within Google CoLab and HuggingFace.vtt 9.2 kB
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  • 01. Getting Started/8. Python Basics, Part 1 Optional.vtt 8.1 kB
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  • 01. Getting Started/9. Activity Python Basics, Part 2 Optional.vtt 8.0 kB
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  • 01. Getting Started/2. Udemy 101 Getting the Most From This Course.vtt 4.2 kB
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  • 01. Getting Started/3. Important note.html 575 Bytes
  • 16. You made it!/2. Don't Forget to Leave a Rating!.html 564 Bytes
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/9. Audio.py 445 Bytes
  • 13. The OpenAI API (Developing with GPT and ChatGPT)/8. Moderation.py 166 Bytes

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