[FreeCourseLab.com] Udemy - Machine Learning, Data Science and Deep Learning with Python

磁力链接/BT种子名称

[FreeCourseLab.com] Udemy - Machine Learning, Data Science and Deep Learning with Python

磁力链接/BT种子简介

种子哈希：29f6a107892304ce88e97cdfd00e87c24f5fadb6
文件大小： 7.38G
已经下载：704次
下载速度：极快
收录时间：2021-04-18
最近下载：2025-05-17

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:29F6A107892304CE88E97CDFD00E87C24F5FADB6
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 世界之窗 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 极乐禁地 91短视频 TikTok成人版 PornHub 草榴社区 91未成年 乱伦巴士 呦乐园 萝莉岛

最近搜索

文件列表

  • 8. Apache Spark Machine Learning on Big Data/8. [Activity] Decision Trees in Spark.mp4 202.6 MB
  • 8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.mp4 180.7 MB
  • 6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.mp4 149.0 MB
  • 10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.mp4 148.5 MB
  • 1. Getting Started/5. Python Basics, Part 1 [Optional].mp4 140.3 MB
  • 8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.mp4 140.3 MB
  • 10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 2.mp4 140.1 MB
  • 5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.mp4 139.0 MB
  • 6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.mp4 138.7 MB
  • 2. Statistics and Probability Refresher, and Python Practise/10. [Exercise] Conditional Probability.mp4 136.7 MB
  • 7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.mp4 135.7 MB
  • 2. Statistics and Probability Refresher, and Python Practise/8. [Activity] A Crash Course in matplotlib.mp4 135.6 MB
  • 10. Deep Learning and Neural Networks/14. The Ethics of Deep Learning.mp4 134.5 MB
  • 1. Getting Started/8. Introducing the Pandas Library [Optional].mp4 134.1 MB
  • 3. Predictive Models/3. [Activity] Multivariate Regression, and Predicting Car Prices.mp4 129.8 MB
  • 2. Statistics and Probability Refresher, and Python Practise/9. [Activity] Covariance and Correlation.mp4 122.4 MB
  • 2. Statistics and Probability Refresher, and Python Practise/7. [Activity] Percentiles and Moments.mp4 119.6 MB
  • 8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4 119.3 MB
  • 8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.mp4 116.9 MB
  • 2. Statistics and Probability Refresher, and Python Practise/4. [Activity] Variation and Standard Deviation.mp4 116.2 MB
  • 6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.mp4 115.1 MB
  • 1. Getting Started/4. [Activity] Installing Enthought Canopy.mp4 114.3 MB
  • 5. Recommender Systems/3. [Activity] Finding Movie Similarities.mp4 113.1 MB
  • 10. Deep Learning and Neural Networks/8. [Activity] Introducing Keras.mp4 112.7 MB
  • 10. Deep Learning and Neural Networks/9. [Activity] Using Keras to Predict Political Affiliations.mp4 109.4 MB
  • 6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.mp4 108.4 MB
  • 7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 107.3 MB
  • 10. Deep Learning and Neural Networks/6. [Activity] Using Tensorflow, Part 1.mp4 107.3 MB
  • 3. Predictive Models/1. [Activity] Linear Regression.mp4 105.4 MB
  • 4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.mp4 103.4 MB
  • 8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).mp4 103.3 MB
  • 11. Final Project/2. Final project review.mp4 103.3 MB
  • 9. Experimental Design/1. AB Testing Concepts.mp4 102.2 MB
  • 10. Deep Learning and Neural Networks/5. Introducing Tensorflow.mp4 101.1 MB
  • 9. Experimental Design/5. AB Test Gotchas.mp4 100.8 MB
  • 4. Machine Learning with Python/10. [Activity] Decision Trees Predicting Hiring Decisions.mp4 100.6 MB
  • 5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.mp4 99.5 MB
  • 10. Deep Learning and Neural Networks/13. [Activity] Using a RNN for sentiment analysis.mp4 99.4 MB
  • 10. Deep Learning and Neural Networks/10. Convolutional Neural Networks (CNN's).mp4 97.6 MB
  • 2. Statistics and Probability Refresher, and Python Practise/3. [Activity] Using mean, median, and mode in Python.mp4 97.2 MB
  • 8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.mp4 94.2 MB
  • 4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 93.4 MB
  • 8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.mp4 91.6 MB
  • 4. Machine Learning with Python/9. Decision Trees Concepts.mp4 90.7 MB
  • 5. Recommender Systems/1. User-Based Collaborative Filtering.mp4 90.6 MB
  • 5. Recommender Systems/6. [Exercise] Improve the recommender's results.mp4 88.3 MB
  • 7. Dealing with Real-World Data/6. [Activity] Detecting outliers.mp4 87.7 MB
  • 9. Experimental Design/3. [Activity] Hands-on With T-Tests.mp4 85.6 MB
  • 10. Deep Learning and Neural Networks/11. [Activity] Using CNN's for handwriting recognition.mp4 84.7 MB
  • 10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.mp4 83.9 MB
  • 7. Dealing with Real-World Data/3. Data Cleaning and Normalization.mp4 82.6 MB
  • 2. Statistics and Probability Refresher, and Python Practise/1. Types of Data.mp4 81.0 MB
  • 1. Getting Started/6. [Activity] Python Basics, Part 2 [Optional].mp4 81.0 MB
  • 2. Statistics and Probability Refresher, and Python Practise/6. Common Data Distributions.mp4 79.0 MB
  • 5. Recommender Systems/2. Item-Based Collaborative Filtering.mp4 78.7 MB
  • 4. Machine Learning with Python/5. K-Means Clustering.mp4 75.4 MB
  • 10. Deep Learning and Neural Networks/12. Recurrent Neural Networks (RNN's).mp4 72.5 MB
  • 8. Apache Spark Machine Learning on Big Data/10. TF IDF.mp4 72.2 MB
  • 10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.mp4 71.2 MB
  • 6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.mp4 71.0 MB
  • 3. Predictive Models/2. [Activity] Polynomial Regression.mp4 70.0 MB
  • 7. Dealing with Real-World Data/1. BiasVariance Tradeoff.mp4 69.5 MB
  • 4. Machine Learning with Python/11. Ensemble Learning.mp4 68.4 MB
  • 9. Experimental Design/2. T-Tests and P-Values.mp4 68.1 MB
  • 10. Deep Learning and Neural Networks/4. Deep Learning Details.mp4 67.3 MB
  • 12. You made it!/1. More to Explore.mp4 67.2 MB
  • 1. Getting Started/1. Introduction.mp4 62.5 MB
  • 2. Statistics and Probability Refresher, and Python Practise/12. Bayes' Theorem.mp4 61.8 MB
  • 11. Final Project/1. Your final project assignment.mp4 61.8 MB
  • 4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 61.0 MB
  • 4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.mp4 60.1 MB
  • 2. Statistics and Probability Refresher, and Python Practise/2. Mean, Median, Mode.mp4 58.9 MB
  • 4. Machine Learning with Python/13. [Activity] Using SVM to cluster people using scikit-learn.mp4 57.7 MB
  • 8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.mp4 57.4 MB
  • 3. Predictive Models/4. Multi-Level Models.mp4 49.8 MB
  • 4. Machine Learning with Python/12. Support Vector Machines (SVM) Overview.mp4 46.9 MB
  • 1. Getting Started/7. Running Python Scripts [Optional].mp4 46.9 MB
  • 4. Machine Learning with Python/3. Bayesian Methods Concepts.mp4 42.7 MB
  • 6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.mp4 42.2 MB
  • 10. Deep Learning and Neural Networks/15. Learning More about Deep Learning.mp4 40.5 MB
  • 7. Dealing with Real-World Data/5. Normalizing numerical data.mp4 40.1 MB
  • 4. Machine Learning with Python/7. Measuring Entropy.mp4 36.7 MB
  • 9. Experimental Design/4. Determining How Long to Run an Experiment.mp4 36.5 MB
  • 2. Statistics and Probability Refresher, and Python Practise/5. Probability Density Function; Probability Mass Function.mp4 31.5 MB
  • 2. Statistics and Probability Refresher, and Python Practise/11. Exercise Solution Conditional Probability of Purchase by Age.mp4 30.1 MB
  • 1. Getting Started/3. [Activity] Getting What You Need.mp4 29.4 MB
  • 1. Getting Started/2. Udemy 101 Getting the Most From This Course.mp4 20.7 MB
  • 1. Getting Started/5. Python Basics, Part 1 [Optional].vtt 32.9 kB
  • 8. Apache Spark Machine Learning on Big Data/8. [Activity] Decision Trees in Spark.vtt 30.1 kB
  • 10. Deep Learning and Neural Networks/8. [Activity] Introducing Keras.vtt 29.3 kB
  • 10. Deep Learning and Neural Networks/9. [Activity] Using Keras to Predict Political Affiliations.vtt 26.7 kB
  • 2. Statistics and Probability Refresher, and Python Practise/8. [Activity] A Crash Course in matplotlib.vtt 26.4 kB
  • 6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.vtt 26.3 kB
  • 6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.vtt 26.2 kB
  • 8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.vtt 26.2 kB
  • 2. Statistics and Probability Refresher, and Python Practise/7. [Activity] Percentiles and Moments.vtt 26.1 kB
  • 2. Statistics and Probability Refresher, and Python Practise/9. [Activity] Covariance and Correlation.vtt 24.0 kB
  • 2. Statistics and Probability Refresher, and Python Practise/4. [Activity] Variation and Standard Deviation.vtt 23.8 kB
  • 2. Statistics and Probability Refresher, and Python Practise/10. [Exercise] Conditional Probability.vtt 23.8 kB
  • 3. Predictive Models/1. [Activity] Linear Regression.vtt 23.7 kB
  • 3. Predictive Models/3. [Activity] Multivariate Regression, and Predicting Car Prices.vtt 23.2 kB
  • 8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).vtt 22.7 kB
  • 11. Final Project/2. Final project review.vtt 22.7 kB
  • 7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.vtt 22.7 kB
  • 7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.vtt 22.0 kB
  • 10. Deep Learning and Neural Networks/13. [Activity] Using a RNN for sentiment analysis.vtt 21.2 kB
  • 5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.vtt 20.9 kB
  • 4. Machine Learning with Python/10. [Activity] Decision Trees Predicting Hiring Decisions.vtt 20.7 kB
  • 8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.vtt 20.7 kB
  • 9. Experimental Design/5. AB Test Gotchas.vtt 20.3 kB
  • 10. Deep Learning and Neural Networks/5. Introducing Tensorflow.vtt 20.2 kB
  • 10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 2.vtt 19.9 kB
  • 10. Deep Learning and Neural Networks/6. [Activity] Using Tensorflow, Part 1.vtt 19.8 kB
  • 8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.vtt 19.6 kB
  • 6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.vtt 19.5 kB
  • 4. Machine Learning with Python/9. Decision Trees Concepts.vtt 19.5 kB
  • 4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.vtt 19.4 kB
  • 1. Getting Started/6. [Activity] Python Basics, Part 2 [Optional].vtt 19.4 kB
  • 9. Experimental Design/1. AB Testing Concepts.vtt 18.7 kB
  • 5. Recommender Systems/3. [Activity] Finding Movie Similarities.vtt 18.6 kB
  • 5. Recommender Systems/2. Item-Based Collaborative Filtering.vtt 18.5 kB
  • 6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.vtt 18.3 kB
  • 10. Deep Learning and Neural Networks/10. Convolutional Neural Networks (CNN's).vtt 18.0 kB
  • 5. Recommender Systems/1. User-Based Collaborative Filtering.vtt 17.9 kB
  • 10. Deep Learning and Neural Networks/14. The Ethics of Deep Learning.vtt 17.9 kB
  • 10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.vtt 17.6 kB
  • 10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.vtt 17.5 kB
  • 10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.vtt 17.2 kB
  • 2. Statistics and Probability Refresher, and Python Practise/3. [Activity] Using mean, median, and mode in Python.vtt 16.9 kB
  • 10. Deep Learning and Neural Networks/12. Recurrent Neural Networks (RNN's).vtt 16.7 kB
  • 10. Deep Learning and Neural Networks/11. [Activity] Using CNN's for handwriting recognition.vtt 16.7 kB
  • 3. Predictive Models/2. [Activity] Polynomial Regression.vtt 16.3 kB
  • 4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.vtt 16.2 kB
  • 8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.vtt 16.2 kB
  • 1. Getting Started/8. Introducing the Pandas Library [Optional].vtt 16.1 kB
  • 4. Machine Learning with Python/5. K-Means Clustering.vtt 15.9 kB
  • 7. Dealing with Real-World Data/3. Data Cleaning and Normalization.vtt 15.8 kB
  • 5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.vtt 15.6 kB
  • 8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.vtt 15.4 kB
  • 10. Deep Learning and Neural Networks/4. Deep Learning Details.vtt 15.2 kB
  • 2. Statistics and Probability Refresher, and Python Practise/1. Types of Data.vtt 15.0 kB
  • 2. Statistics and Probability Refresher, and Python Practise/6. Common Data Distributions.vtt 14.9 kB
  • 7. Dealing with Real-World Data/6. [Activity] Detecting outliers.vtt 14.3 kB
  • 8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.vtt 14.3 kB
  • 4. Machine Learning with Python/11. Ensemble Learning.vtt 13.5 kB
  • 7. Dealing with Real-World Data/1. BiasVariance Tradeoff.vtt 13.4 kB
  • 8. Apache Spark Machine Learning on Big Data/10. TF IDF.vtt 13.0 kB
  • 1. Getting Started/4. [Activity] Installing Enthought Canopy.vtt 12.7 kB
  • 9. Experimental Design/3. [Activity] Hands-on With T-Tests.vtt 12.7 kB
  • 9. Experimental Design/2. T-Tests and P-Values.vtt 12.3 kB
  • 5. Recommender Systems/6. [Exercise] Improve the recommender's results.vtt 12.3 kB
  • 4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.vtt 12.2 kB
  • 2. Statistics and Probability Refresher, and Python Practise/2. Mean, Median, Mode.vtt 12.0 kB
  • 6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.vtt 11.4 kB
  • 4. Machine Learning with Python/13. [Activity] Using SVM to cluster people using scikit-learn.vtt 11.1 kB
  • 4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.vtt 10.7 kB
  • 2. Statistics and Probability Refresher, and Python Practise/12. Bayes' Theorem.vtt 10.7 kB
  • 8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.vtt 10.7 kB
  • 11. Final Project/1. Your final project assignment.vtt 10.4 kB
  • 3. Predictive Models/4. Multi-Level Models.vtt 9.9 kB
  • 4. Machine Learning with Python/12. Support Vector Machines (SVM) Overview.vtt 9.2 kB
  • 1. Getting Started/7. Running Python Scripts [Optional].vtt 8.4 kB
  • 6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.vtt 8.3 kB
  • 4. Machine Learning with Python/3. Bayesian Methods Concepts.vtt 8.2 kB
  • 9. Experimental Design/4. Determining How Long to Run an Experiment.vtt 7.8 kB
  • 12. You made it!/3. Bonus Lecture Discounts to continue your journey!.html 7.6 kB
  • 7. Dealing with Real-World Data/5. Normalizing numerical data.vtt 7.2 kB
  • 2. Statistics and Probability Refresher, and Python Practise/5. Probability Density Function; Probability Mass Function.vtt 7.1 kB
  • 12. You made it!/1. More to Explore.vtt 6.8 kB
  • 4. Machine Learning with Python/7. Measuring Entropy.vtt 6.5 kB
  • 2. Statistics and Probability Refresher, and Python Practise/11. Exercise Solution Conditional Probability of Purchase by Age.vtt 4.6 kB
  • 1. Getting Started/1. Introduction.vtt 4.3 kB
  • 1. Getting Started/3. [Activity] Getting What You Need.vtt 4.3 kB
  • 1. Getting Started/2. Udemy 101 Getting the Most From This Course.vtt 3.6 kB
  • 8. Apache Spark Machine Learning on Big Data/2. Spark installation notes for MacOS and Linux users.html 3.6 kB
  • 10. Deep Learning and Neural Networks/15. Learning More about Deep Learning.vtt 2.8 kB
  • 4. Machine Learning with Python/8. [Activity] Install GraphViz.html 1.5 kB
  • 8. Apache Spark Machine Learning on Big Data/1. Warning about Java 11 and Spark 2.4!.html 615 Bytes
  • 12. You made it!/2. Don't Forget to Leave a Rating!.html 564 Bytes
  • 6. More Data Mining and Machine Learning Techniques/6.2 Pac-Man Example.html 145 Bytes
  • 6. More Data Mining and Machine Learning Techniques/6.1 Cat and Mouse Example.html 140 Bytes
  • [FreeCourseLab.com].url 126 Bytes
  • 6. More Data Mining and Machine Learning Techniques/6.3 Python Markov Decision Process Toolbox.html 119 Bytes
  • 1. Getting Started/3.1 Course Facebook Group.html 109 Bytes
  • 8. Apache Spark Machine Learning on Big Data/3.1 winutils.exe.html 108 Bytes
  • 8. Apache Spark Machine Learning on Big Data/4.1 winutils.exe.html 108 Bytes
  • 1. Getting Started/3.2 Course materials and setup steps.html 100 Bytes
  • 1. Getting Started/4.1 Enthought Canopy website.html 86 Bytes

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！
>