Udemy - Machine Learning, Data Science and Deep Learning with Python

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[FreeAllCourse.Com] Udemy - Machine Learning, Data Science and Deep Learning with Python 1. Getting Started
  • 1. Introduction.mp4 (59.6 MB)
  • 1. Introduction.srt (4.7 KB)
  • 10. [Activity] Python Basics, Part 4 [Optional].mp4 (21.1 MB)
  • 10. [Activity] Python Basics, Part 4 [Optional].srt (21.1 MB)
  • 11. Introducing the Pandas Library [Optional].mp4 (123.1 MB)
  • 11. Introducing the Pandas Library [Optional].srt (18.0 KB)
  • 2. Udemy 101 Getting the Most From This Course.mp4 (19.8 MB)
  • 2. Udemy 101 Getting the Most From This Course.srt (4.0 KB)
  • 3. Installation Getting Started.html (0.3 KB)
  • 4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4 (102.8 MB)
  • 4. [Activity] WINDOWS Installing and Using Anaconda & Course Materials.srt (18.9 KB)
  • 5. [Activity] MAC Installing and Using Anaconda & Course Materials.mp4 (96.5 MB)
  • 5. [Activity] MAC Installing and Using Anaconda & Course Materials.srt (14.5 KB)
  • 6. [Activity] LINUX Installing and Using Anaconda & Course Materials.mp4 (80.2 MB)
  • 6. [Activity] LINUX Installing and Using Anaconda & Course Materials.srt (14.7 KB)
  • 7. Python Basics, Part 1 [Optional].mp4 (33.0 MB)
  • 7. Python Basics, Part 1 [Optional].srt (7.8 KB)
  • 8. [Activity] Python Basics, Part 2 [Optional].mp4 (20.6 MB)
  • 8. [Activity] Python Basics, Part 2 [Optional].srt (7.6 KB)
  • 9. [Activity] Python Basics, Part 3 [Optional].mp4 (10.1 MB)
  • 9. [Activity] Python Basics, Part 3 [Optional].srt (4.2 KB)
10. Deep Learning and Neural Networks
  • 1. Deep Learning Pre-Requisites.mp4 (74.2 MB)
  • 1. Deep Learning Pre-Requisites.srt (21.5 KB)
  • 10. [Activity] Using Keras to Predict Political Affiliations.mp4 (88.2 MB)
  • 10. [Activity] Using Keras to Predict Political Affiliations.srt (21.1 KB)
  • 11. Convolutional Neural Networks (CNN's).mp4 (93.1 MB)
  • 11. Convolutional Neural Networks (CNN's).srt (19.9 KB)
  • 12. [Activity] Using CNN's for handwriting recognition.mp4 (69.6 MB)
  • 12. [Activity] Using CNN's for handwriting recognition.srt (13.8 KB)
  • 13. Recurrent Neural Networks (RNN's).mp4 (69.2 MB)
  • 13. Recurrent Neural Networks (RNN's).srt (18.5 KB)
  • 14. [Activity] Using a RNN for sentiment analysis.mp4 (81.4 MB)
  • 14. [Activity] Using a RNN for sentiment analysis.srt (16.8 KB)
  • 15. [Activity] Transfer Learning.mp4 (115.3 MB)
  • 15. [Activity] Transfer Learning.srt (21.5 KB)
  • 16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 (18.4 MB)
  • 16. Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.srt (8.3 KB)
  • 17. Deep Learning Regularization with Dropout and Early Stopping.mp4 (33.6 MB)
  • 17. Deep Learning Regularization with Dropout and Early Stopping.srt (12.0 KB)
  • 18. The Ethics of Deep Learning.mp4 (128.2 MB)
  • 18. The Ethics of Deep Learning.srt (19.8 KB)
  • 19. Learning More about Deep Learning.mp4 (38.6 MB)
  • 19. Learning More about Deep Learning.srt (3.1 KB)
  • 2. The History of Artificial Neural Networks.mp4 (80.0 MB)
  • 2. The History of Artificial Neural Networks.srt (19.1 KB)
  • 3. [Activity] Deep Learning in the Tensorflow Playground.mp4 (141.6 MB)
  • 3. [Activity] Deep Learning in the Tensorflow Playground.srt (19.7 KB)
  • 4. Deep Learning Details.mp4 (64.2 MB)
  • 4. Deep Learning Details.srt (16.8 KB)
  • 5. Introducing Tensorflow.mp4 (64.2 MB)
  • 5. Introducing Tensorflow.srt (20.2 KB)
  • 6. Important note about Tensorflow 2.html (0.6 KB)
  • 7. [Activity] Using Tensorflow, Part 1.mp4 (118.2 MB)
  • 7. [Activity] Using Tensorflow, Part 1.srt (23.5 KB)
  • 8. [Activity] Using Tensorflow, Part 2.mp4 (104.5 MB)
  • 8. [Activity] Using Tensorflow, Part 2.srt (21.6 KB)
  • 9. [Activity] Introducing Keras.mp4 (92.1 MB)
  • 9. [Activity] Introducing Keras.srt (23.7 KB)
11. Final Project
  • 1. Your final project assignment.mp4 (51.6 MB)
  • 1. Your final project assignment.srt (11.6 KB)
  • 2. Final project review.mp4 (98.5 MB)
  • 2. Final project review.srt (24.5 KB)
12. You made it!
  • 1. More to Explore.mp4 (64.1 MB)
  • 1. More to Explore.srt (7.2 KB)
  • 2. Don't Forget to Leave a Rating!.html (0.6 KB)
  • 3. Bonus Lecture More courses to explore!.html (7.4 KB)
2. Statistics and Probability Refresher, and Python Practice
  • 1. Types of Data.mp4 (77.2 MB)
  • 1. Types of Data.srt (16.2 KB)
  • 10. [Activity] Covariance and Correlation.mp4 (116.7 MB)
  • 10. [Activity] Covariance and Correlation.srt (25.9 KB)
  • 11. [Exercise] Conditional Probability.mp4 (125.1 MB)
  • 11. [Exercise] Conditional Probability.srt (28.4 KB)
  • 12. Exercise Solution Conditional Probability of Purchase by Age.mp4 (22.0 MB)
  • 12. Exercise Solution Conditional Probability of Purchase by Age.srt (4.0 KB)
  • 13. Bayes' Theorem.mp4 (58.9 MB)
  • 13. Bayes' Theorem.srt (11.5 KB)
  • 2. Mean, Median, Mode.mp4 (56.1 MB)
  • 2. Mean, Median, Mode.srt (13.0 KB)
  • 3. [Activity] Using mean, median, and mode in Python.mp4 (61.9 MB)
  • 3. [Activity] Using mean, median, and mode in Python.srt (15.0 KB)
  • 4. [Activity] Variation and Standard Deviation.mp4 (110.8 MB)
  • 4. [Activity] Variation and Standard Deviation.srt (25.8 KB)
  • 5. Probability Density Function; Probability Mass Function.mp4 (30.1 MB)
  • 5. Probability Density Function; Probability Mass Function.srt (7.6 KB)
  • 6. Common Data Distributions.mp4 (75.4 MB)
  • 6. Common Data Distributions.srt (16.1 KB)
  • 7. [Activity] Percentiles and Moments.mp4 (114.0 MB)
  • 7. [Activity] Percentiles and Moments.srt (28.3 KB)
  • 8. [Activity] A Crash Course in matplotlib.mp4 (129.3 MB)
  • 8. [Activity] A Crash Course in matplotlib.srt (28.6 KB)
  • 9. [Activity] Advanced Visualization with Seaborn.mp4 (147.8 MB)
  • 9. [Activity] Advanced Visualization with Seaborn.srt (30.0 KB)
3. Predictive Models
  • 1. [Activity] Linear Regression.mp4 (100.5 MB)
  • 1. [Activity] Linear Regression.srt (25.7 KB)
  • 2. [Activity] Polynomial Regression.mp4 (66.8 MB)

Description

Machine Learning, Data Science and Deep Learning with Python



Complete hands-on machine learning tutorial with data science, Tensorflow, artificial intelligence, and neural networks

What you'll learn:

Build artificial neural networks with Tensorflow and Keras
Classify images, data, and sentiments using deep learning
Make predictions using linear regression, polynomial regression, and multivariate regression
Data Visualization with MatPlotLib and Seaborn
Implement machine learning at massive scale with
Apache Spark's MLLib
Understand reinforcement learning - and how to build a
Pac-Man bot

Created by Sundog Education by Frank Kane, Frank Kane
Last updated 12/2019
English

For More Updated Course Visit: freeallcourse.com



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7.7 GB
seeders:9
leechers:17
Udemy - Machine Learning, Data Science and Deep Learning with Python

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Download torrent
7.7 GB
seeders:9
leechers:17
Udemy - Machine Learning, Data Science and Deep Learning with Python

Torrent hash: 0AABAF0A4D614C15524F6E0A51897B3E70DF722D