Deep Learning Foundation Linear Regression and Statistics (Updated)

"softddl.org"
28-07-2020, 11:14
Rating:
0
0 vote

  • Deep Learning Foundation  Linear Regression and Statistics (Updated)
    Deep Learning Foundation : Linear Regression and Statistics
    Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 4.15 GB
    Genre: eLearning Video | Duration: 39 lectures (5 hour, 37 mins) | Language: English

Deep Learning Foundation  Linear Regression and Statistics (Updated) Deep Learning Foundation : Linear Regression and Statistics Video: .mp4 (1280x720, 30 fps(r)) | Audio: aac, 44100 Hz, 2ch | Size: 4.15 GB Genre: eLearning Video | Duration: 39 lectures (5 hour, 37 mins) | Language: English Data science : Learn statistics behind linear regression and build your own working program from scratch in Python. What you'll learn Linear regression statistics basics Assumptions of linear regression hypothesis testing sampling Program your own version of a linear regression model in Python Derive and solve a linear regression model, and apply it appropriately to data science problems Requirements Jupyter notebook and simple python programming Description Hi Everyone welcome to new course which is created to sharpen your linear regression and statistical basics. linear regression is starting point for a data science this course focus is on making your foundation strong for deep learning and machine learning algorithms. In this course I have explained hypothesis testing, Unbiased estimators, Statistical test , Gradient descent. End of the course you will be able to code your own regression algorithm from scratch. Who this course is for: Python developers curious about data science data science and machine leaning engineers Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me
https://uploadgig.com/file/download/77ff84d22D29Ec40/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part1.rar https://uploadgig.com/file/download/d3d4411d1a3e92FE/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part2.rar https://uploadgig.com/file/download/b8bce2Fef3252ffD/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part3.rar https://uploadgig.com/file/download/b5243868569feae7/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part4.rar https://uploadgig.com/file/download/c74bF1a07e563787/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part5.rar https://rapidgator.net/file/0cc6e5fd20901693e8f14b11cdf5137d/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part1.rar https://rapidgator.net/file/1dd5dd59ba88f1b0bf1b41136a605b56/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part2.rar https://rapidgator.net/file/23e14f28cad04375b07590c90bc92a3e/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part3.rar https://rapidgator.net/file/c2f0e75cdcdfadcd6e552f9c5808a83f/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part4.rar https://rapidgator.net/file/c79e0f838ae9d5147278eea3156c617e/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part5.rar http://nitroflare.com/view/D218B6237CEB5E9/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part1.rar http://nitroflare.com/view/E8FC7D726566886/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part2.rar http://nitroflare.com/view/06CDB0FD4DC0923/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part3.rar http://nitroflare.com/view/A2AA01472AA0232/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part4.rar http://nitroflare.com/view/F506C5BC5F97F2A/j2uuy.Deep.Learning.Foundation..Linear.Regression.and.Statistics.Updated.part5.rar
Download now LINK

Download now LINK
 
Comments
The minimum comment length is 50 characters. comments are moderated
There are no comments yet. You can be the first!
Download free » Tutorials » Deep Learning Foundation Linear Regression and Statistics (Updated)
Copyright holders