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[FreeCourseSite.com] Udemy - Data Science Masterclass 2021 Build 30 Real World Projects

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种子名称: [FreeCourseSite.com] Udemy - Data Science Masterclass 2021 Build 30 Real World Projects
文件类型: 视频
文件数目: 149个文件
文件大小: 10.28 GB
收录时间: 2023-9-19 05:09
已经下载: 3
资源热度: 164
最近下载: 2024-11-26 09:55

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[FreeCourseSite.com] Udemy - Data Science Masterclass 2021 Build 30 Real World Projects.torrent
  • 1. Introduction To The Course/1. Introduction to the course.mp431.32MB
  • 1. Introduction To The Course/2. Introduction Course Outline.mp460.93MB
  • 1. Introduction To The Course/3. Udemy Course Feedback.mp42.03MB
  • 10. Project-9 Bird Species Prediction App/1. Introduction.mp421.47MB
  • 10. Project-9 Bird Species Prediction App/2. Improting Libraries And Data.mp457.53MB
  • 10. Project-9 Bird Species Prediction App/3. Data processing.mp430.93MB
  • 10. Project-9 Bird Species Prediction App/4. Creating Machine Learning Model.mp494.29MB
  • 10. Project-9 Bird Species Prediction App/5. Creating A Flask App.mp472MB
  • 11. Project-10 Intel Image Classification App/1. Introduction.mp425.71MB
  • 11. Project-10 Intel Image Classification App/2. Importing and processing data.mp465.79MB
  • 11. Project-10 Intel Image Classification App/3. Creating a Model.mp488.4MB
  • 11. Project-10 Intel Image Classification App/4. Creating a Flask App.mp459.44MB
  • 12. Project-11 Sentiment Analysis Using Logistic Regression/1. Introduction to Sentiment Analysis.mp49.17MB
  • 12. Project-11 Sentiment Analysis Using Logistic Regression/2. Project Notebook Google Colab.mp4140.82MB
  • 12. Project-11 Sentiment Analysis Using Logistic Regression/3. Building Django App.mp471.94MB
  • 12. Project-11 Sentiment Analysis Using Logistic Regression/4. Deploying App In Heroku.mp479.14MB
  • 13. Project-12 Attrition Rate Django App/1. Introduction.mp49.25MB
  • 13. Project-12 Attrition Rate Django App/2. Creating Colab Notebook.mp4213.79MB
  • 13. Project-12 Attrition Rate Django App/3. Creating Django Application.mp485.07MB
  • 13. Project-12 Attrition Rate Django App/4. Deploy the app in Heroku.mp460.5MB
  • 14. Project-13 Project To Find Legendary Pokemon/1. Introduction.mp410.3MB
  • 14. Project-13 Project To Find Legendary Pokemon/2. Creating Colab Notebook.mp4177.23MB
  • 14. Project-13 Project To Find Legendary Pokemon/3. Creating Django Application.mp4108.18MB
  • 14. Project-13 Project To Find Legendary Pokemon/4. Deploy the app in Heroku.mp462.23MB
  • 15. Project-14 Create Face Detection Application/1. Introduction.mp411.39MB
  • 15. Project-14 Create Face Detection Application/2. Creating The Face App Using OpenCV 1.mp4103.67MB
  • 15. Project-14 Create Face Detection Application/3. Creating The Face App Using OpenCV 2.mp465.68MB
  • 15. Project-14 Create Face Detection Application/4. Creating The Face App Using OpenCV 3.mp494.2MB
  • 16. Project-15 Cats Vs Dogs Image Classification App/1. Introduction To Cats Vs Dogs Classification.mp413.18MB
  • 16. Project-15 Cats Vs Dogs Image Classification App/2. Creating Project Notebook.mp4244.31MB
  • 16. Project-15 Cats Vs Dogs Image Classification App/3. Building Model.mp474.76MB
  • 16. Project-15 Cats Vs Dogs Image Classification App/4. Building Flask App.mp451.9MB
  • 16. Project-15 Cats Vs Dogs Image Classification App/5. Flask App Deployment.mp465.82MB
  • 17. Project-16 Customer Revenue Prediction/1. Introduction To Customer Revenue Prediction.mp413.29MB
  • 17. Project-16 Customer Revenue Prediction/2. Colab Notebook.mp4201.73MB
  • 17. Project-16 Customer Revenue Prediction/3. Creating Flask App.mp4117.96MB
  • 17. Project-16 Customer Revenue Prediction/4. Deploying Flask App.mp466.45MB
  • 18. Project-17 Gender From Voice Prediction/1. Introduction.mp410.54MB
  • 18. Project-17 Gender From Voice Prediction/2. Creating Project Notebook.mp4242.9MB
  • 18. Project-17 Gender From Voice Prediction/3. Creating Project App Django.mp4106.68MB
  • 18. Project-17 Gender From Voice Prediction/4. Deploying The App.mp461.14MB
  • 19. Project-18 Restaurant Recommendation System/1. Introduction.mp421.27MB
  • 19. Project-18 Restaurant Recommendation System/2. Creating Colab Notebook.mp4116.67MB
  • 19. Project-18 Restaurant Recommendation System/3. Exploratory Data Analysis.mp485.45MB
  • 19. Project-18 Restaurant Recommendation System/4. Data Analysis 2.mp4242.84MB
  • 2. Project-1 Pan Card Tempering Detector Application/1. Introduction.mp416.2MB
  • 2. Project-1 Pan Card Tempering Detector Application/2. Loading libraries and dataset.mp4106.87MB
  • 2. Project-1 Pan Card Tempering Detector Application/3. Creating the pancard detector with opencv.mp4106.87MB
  • 2. Project-1 Pan Card Tempering Detector Application/4. Creating the Flask App.mp414.94MB
  • 2. Project-1 Pan Card Tempering Detector Application/5. Creating Important functions.mp429.11MB
  • 2. Project-1 Pan Card Tempering Detector Application/6. Deploy the app in Heroku.mp439.07MB
  • 2. Project-1 Pan Card Tempering Detector Application/7. Testing the deployed pan card detector..mp45.72MB
  • 20. Project-19 Check Happiness Ranking Using Machine Learning/1. Introduction.mp416.34MB
  • 20. Project-19 Check Happiness Ranking Using Machine Learning/2. Project Notebook.mp4240.47MB
  • 20. Project-19 Check Happiness Ranking Using Machine Learning/3. Creating Django App.mp4138.4MB
  • 20. Project-19 Check Happiness Ranking Using Machine Learning/4. Deploying Django App.mp459.41MB
  • 21. Project-20 Predicting Forest Fire - Machine Learning/1. Introduction.mp419.43MB
  • 21. Project-20 Predicting Forest Fire - Machine Learning/2. Project Notebook.mp4207.16MB
  • 21. Project-20 Predicting Forest Fire - Machine Learning/3. Project Notebook Part 2.mp476.38MB
  • 21. Project-20 Predicting Forest Fire - Machine Learning/4. Creating Django App.mp4117.09MB
  • 21. Project-20 Predicting Forest Fire - Machine Learning/5. Deploying Django App.mp457.63MB
  • 22. Project-21 Black Friday Sale Prediction/1. Importing libraries and data.mp436.43MB
  • 22. Project-21 Black Friday Sale Prediction/2. Understanding data.mp437.57MB
  • 22. Project-21 Black Friday Sale Prediction/3. Data visulaization and data preprocessing.mp4108.93MB
  • 22. Project-21 Black Friday Sale Prediction/4. Model building part-1.mp449.27MB
  • 22. Project-21 Black Friday Sale Prediction/5. Model building part-2.mp458.87MB
  • 23. Project-22 Sentiment Analysis Project/1. Importing libraries and data.mp465.16MB
  • 23. Project-22 Sentiment Analysis Project/2. Text normalization.mp474.88MB
  • 23. Project-22 Sentiment Analysis Project/3. Lemmatization.mp445.38MB
  • 23. Project-22 Sentiment Analysis Project/4. Data preprocessing.mp4103.65MB
  • 23. Project-22 Sentiment Analysis Project/5. Model Building.mp487.16MB
  • 24. Project-23 Parkinson Syndrome Prediction/1. Importing libraries and data.mp439.69MB
  • 24. Project-23 Parkinson Syndrome Prediction/2. Understanding the data.mp473.4MB
  • 24. Project-23 Parkinson Syndrome Prediction/3. Data visualization.mp455MB
  • 24. Project-23 Parkinson Syndrome Prediction/4. Model building part 1.mp474.62MB
  • 24. Project-23 Parkinson Syndrome Prediction/5. Model building part 2.mp4104.82MB
  • 25. Project-24 Fake News Classifier - NLP/1. Importing libraries and data.mp432.13MB
  • 25. Project-24 Fake News Classifier - NLP/2. data preprocessing.mp440.74MB
  • 25. Project-24 Fake News Classifier - NLP/3. Text cleaning.mp461.04MB
  • 25. Project-24 Fake News Classifier - NLP/4. Vectorizer.mp418.6MB
  • 25. Project-24 Fake News Classifier - NLP/5. Model Building.mp4101.92MB
  • 26. Project-25 Toxic Comment Classifier/1. Importing libraries and data.mp447.87MB
  • 26. Project-25 Toxic Comment Classifier/2. Understanding data.mp431.94MB
  • 26. Project-25 Toxic Comment Classifier/3. data visualization and preprocessing.mp480.5MB
  • 26. Project-25 Toxic Comment Classifier/4. Balancing the target column.mp451.53MB
  • 26. Project-25 Toxic Comment Classifier/5. Model building.mp475.53MB
  • 26. Project-25 Toxic Comment Classifier/6. Model evaluation.mp444.54MB
  • 27. Project-26 Movie Ratings Prediction (IMDB)/1. Importing libraries and data.mp485.65MB
  • 27. Project-26 Movie Ratings Prediction (IMDB)/2. Understanding data.mp492.16MB
  • 27. Project-26 Movie Ratings Prediction (IMDB)/3. Data visualization.mp468.63MB
  • 27. Project-26 Movie Ratings Prediction (IMDB)/4. Data preprocessing.mp470.52MB
  • 27. Project-26 Movie Ratings Prediction (IMDB)/5. Model building.mp4114.48MB
  • 28. Project-27 Air Quality Prediction/1. Importing libraries and data.mp459.56MB
  • 28. Project-27 Air Quality Prediction/2. Understanding data.mp471.76MB
  • 28. Project-27 Air Quality Prediction/3. data visualization.mp492.58MB
  • 28. Project-27 Air Quality Prediction/4. data preprocessing.mp474.46MB
  • 28. Project-27 Air Quality Prediction/5. Feature Engineering.mp4113.87MB
  • 28. Project-27 Air Quality Prediction/6. Model building part1.mp4123.41MB
  • 28. Project-27 Air Quality Prediction/7. Model building part2.mp449.51MB
  • 29. Project-28 Covid-19 Case Analysis/1. Importing libraries and data.mp462.08MB
  • 29. Project-28 Covid-19 Case Analysis/2. data preprocessing.mp4119.12MB
  • 29. Project-28 Covid-19 Case Analysis/3. Data Analysis.mp4102.51MB
  • 29. Project-28 Covid-19 Case Analysis/4. Data Analysis part2.mp4134.98MB
  • 3. Project-2 Dog breed prediction application/1. Introduction.mp415.91MB
  • 3. Project-2 Dog breed prediction application/2. Importing the data and libraries.mp456.79MB
  • 3. Project-2 Dog breed prediction application/3. Data Preprocessing.mp429.95MB
  • 3. Project-2 Dog breed prediction application/4. Build and Train Model.mp473.27MB
  • 3. Project-2 Dog breed prediction application/5. Testing the model.mp418.76MB
  • 3. Project-2 Dog breed prediction application/6. Creating the Flask App.mp428.11MB
  • 3. Project-2 Dog breed prediction application/7. Running the app in system.mp417.28MB
  • 30. Project-29 Customer Churning Prediction/1. Importing libraries and data.mp4113.33MB
  • 30. Project-29 Customer Churning Prediction/2. Understanding data.mp468.94MB
  • 30. Project-29 Customer Churning Prediction/3. data visualization.mp4160.48MB
  • 30. Project-29 Customer Churning Prediction/4. Model building.mp4147.29MB
  • 30. Project-29 Customer Churning Prediction/5. Hypertuning.mp4102.25MB
  • 31. Project-30 Create A Chatbot Using NLP/1. Importing libraries and data.mp439.09MB
  • 31. Project-30 Create A Chatbot Using NLP/2. Understanding data.mp450.67MB
  • 31. Project-30 Create A Chatbot Using NLP/3. data visualization.mp474.31MB
  • 31. Project-30 Create A Chatbot Using NLP/4. text normalization.mp4112.89MB
  • 31. Project-30 Create A Chatbot Using NLP/5. Creating a application.mp476.9MB
  • 4. Project-3 Create Image Watermarking Application/1. Introduction To Image Watermarking.mp415.11MB
  • 4. Project-3 Create Image Watermarking Application/2. Importing libraries and logo.mp425.17MB
  • 4. Project-3 Create Image Watermarking Application/3. Create text and image watermark.mp475.98MB
  • 4. Project-3 Create Image Watermarking Application/4. Creating the app.mp463.32MB
  • 4. Project-3 Create Image Watermarking Application/5. Deploying the app in Heroku.mp430MB
  • 5. Project-4 Traffic sign classification/1. Introduction to traffic sign classification.mp430.82MB
  • 5. Project-4 Traffic sign classification/2. Importing the data and libraries.mp457.45MB
  • 5. Project-4 Traffic sign classification/3. Image processing.mp445.03MB
  • 5. Project-4 Traffic sign classification/4. Creating and testing the model.mp462.05MB
  • 5. Project-4 Traffic sign classification/5. Creating model for test set.mp447.4MB
  • 6. Project-5 Text Extraction From Image Application/1. Introduction.mp418.51MB
  • 6. Project-5 Text Extraction From Image Application/2. Importing libraries and data.mp433.94MB
  • 6. Project-5 Text Extraction From Image Application/3. Extracting the test from image.mp440.63MB
  • 6. Project-5 Text Extraction From Image Application/4. Modifiying the extractor.mp469.94MB
  • 6. Project-5 Text Extraction From Image Application/5. Creating the extractor app.mp438.63MB
  • 6. Project-5 Text Extraction From Image Application/6. Running the extractor app.mp414.86MB
  • 7. Project-6 Plant Disease Prediction Application/1. Introduction.mp435.11MB
  • 7. Project-6 Plant Disease Prediction Application/2. Importing libraries and data.mp431.78MB
  • 7. Project-6 Plant Disease Prediction Application/3. Understanding the data.mp449.79MB
  • 7. Project-6 Plant Disease Prediction Application/4. Model building.mp476.83MB
  • 7. Project-6 Plant Disease Prediction Application/5. Creating an app using streamlit.mp451.26MB
  • 8. Project-7 Vehicle Detection & Counting OpenCV, Flask App/1. Introduction To Vehicle Detection.mp425.78MB
  • 8. Project-7 Vehicle Detection & Counting OpenCV, Flask App/2. Importing libraries and data.mp422.43MB
  • 8. Project-7 Vehicle Detection & Counting OpenCV, Flask App/3. Transforing Images and creating output.mp499.08MB
  • 8. Project-7 Vehicle Detection & Counting OpenCV, Flask App/4. Creating a Flask App.mp483.97MB
  • 9. Project-8 Create A Face Swapping Application/1. Introduction.mp420.38MB
  • 9. Project-8 Create A Face Swapping Application/2. Importing libraries and data.mp436.14MB
  • 9. Project-8 Create A Face Swapping Application/3. Data preprocessing and creating output.mp4127.52MB
  • 9. Project-8 Create A Face Swapping Application/4. Creating A Flask App.mp478.45MB