Udemy - Become Certified Machine Learning Professional

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size1.3 GB
  • Uploaded Byfreecoursewb
  • Downloads53
  • Last checkedNov. 19th '21
  • Date uploadedNov. 17th '21
  • Seeders 7
  • Leechers5

Infohash : 408BFC7798D5D65E5E1DAC387DD28869757C1E2C

Become Certified Machine Learning Professional



https://CourseLala.com

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 1.34 GB | Duration: 5h 48m
From beginning to pro level
What you'll learn
You will get deep knowledge about Machine Learning
You will get overview of Natural Language Processing
You will be able to apply machine learning models according to problem
You will be able to manage and clean data before applying machine learning

Description
This course is designed for beginner to pro-level machine learning engineers. In this course, we will start from the very basics and will go to an advanced level. I have designed this course in a way that everybody can understand easily. Additionally, I have given tutorials for python,Numpy and matplotlib because these are very important for machine learning. In the end, we will do some practical projects and will apply all the concepts which we have learnt so far. We will see these concepts

Linear Regression(Single Variable and Multiple Variable)

Logistic Regression(Single Variable and Multiple Variable)

Files:

[ CourseLala.com ] Udemy - Become Certified Machine Learning Professional
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction
    • 1. Introduction.mp4 (19.4 MB)
    • 1. Introduction.srt (1.2 KB)
    • 10. Strings(Part - 1).mp4 (23.4 MB)
    • 10. Strings(Part - 1).srt (7.5 KB)
    • 11. Strings(Part - 2).mp4 (13.0 MB)
    • 11. Strings(Part - 2).srt (4.6 KB)
    • 12. Decision Making statements.mp4 (37.0 MB)
    • 12. Decision Making statements.srt (10.8 KB)
    • 13. Functions.mp4 (11.7 MB)
    • 13. Functions.srt (4.3 KB)
    • 14. Data Structures Tuple.mp4 (19.0 MB)
    • 14. Data Structures Tuple.srt (7.5 KB)
    • 15. Lists.mp4 (23.1 MB)
    • 15. Lists.srt (8.7 KB)
    • 16. Dictionary.mp4 (20.1 MB)
    • 16. Dictionary.srt (6.3 KB)
    • 17. Sets.mp4 (17.0 MB)
    • 17. Sets.srt (5.6 KB)
    • 18. Introduction to Libraries.mp4 (5.6 MB)
    • 18. Introduction to Libraries.srt (2.5 KB)
    • 19. Numpy (Part - 1).mp4 (24.1 MB)
    • 19. Numpy (Part - 1).srt (7.9 KB)
    • 2. AI VS ML VS DL.mp4 (15.8 MB)
    • 2. AI VS ML VS DL.srt (3.2 KB)
    • 20. Numpy (Part - 2).mp4 (31.3 MB)
    • 20. Numpy (Part - 2).srt (10.9 KB)
    • 21. Numpy (Part - 3).mp4 (26.5 MB)
    • 21. Numpy (Part - 3).srt (9.6 KB)
    • 22. Pandas(Part - 1).mp4 (24.8 MB)
    • 22. Pandas(Part - 1).srt (8.3 KB)
    • 23. Pandas(Part - 2).mp4 (24.9 MB)
    • 23. Pandas(Part - 2).srt (8.0 KB)
    • 24. Matplotlib.mp4 (44.9 MB)
    • 24. Matplotlib.srt (14.4 KB)
    • 3. Types of Machine Learning.mp4 (30.0 MB)
    • 3. Types of Machine Learning.srt (5.0 KB)
    • 4. Workflow and Tools.mp4 (16.5 MB)
    • 4. Workflow and Tools.srt (6.4 KB)
    • 5. How to download and use anaconda.mp4 (16.5 MB)
    • 5. How to download and use anaconda.srt (3.8 KB)
    • 6. Retrieve data.mp4 (14.4 MB)
    • 6. Retrieve data.srt (4.1 KB)
    • 6.1 STOCKDATA.csv (0.2 KB)
    • 6.2 STOCKDATA.xlsx (10.5 KB)
    • 7. Variable and Data type.mp4 (15.1 MB)
    • 7. Variable and Data type.srt (5.9 KB)
    • 8. Operators.mp4 (22.8 MB)
    • 8. Operators.srt (7.2 KB)
    • 9. Keywords and Identifiers.mp4 (11.8 MB)
    • 9. Keywords and Identifiers.srt (4.7 KB)
    2. Data Preprocessing
    • 1. What is feature Engineering.mp4 (10.0 MB)
    • 1. What is feature Engineering.srt (3.9 KB)
    • 2. Outlier detection using standard deviation.mp4 (22.8 MB)
    • 2. Outlier detection using standard deviation.srt (7.5 KB)
    • 3. Outlier detection using percentile method.mp4 (18.8 MB)
    • 3. Outlier detection using percentile method.srt (7.4 KB)
    • 4. Handle Missing Data.mp4 (41.1 MB)
    • 4. Handle Missing Data.srt (7.8 KB)
    3. Supervised learning Regression models
    • 1. Linear Regression Single Variable.mp4 (16.4 MB)
    • 1. Linear Regression Single Variable.srt (4.9 KB)
    • 2. Linear Regression Multiple Variable.mp4 (15.6 MB)
    • 2. Linear Regression Multiple Variable.srt (3.9 KB)
    • 3. Predict function.mp4 (9.9 MB)
    • 3. Predict function.srt (3.8 KB)
    • 4. Train Test Split Method.mp4 (12.9 MB)
    • 4. Train Test Split Method.srt (3.5 KB)
    • 5. Logistic Regression Binary Class Classification.mp4 (25.1 MB)
    • 5. Logistic Regression Binary Class Classification.srt (6.7 KB)
    • 6. Logistic Regression Multiple Class Classification.mp4 (24.1 MB)
    • 6. Logistic Regression Multiple Class Classification.srt (4.3 KB)
    • 7. Save and Load model.mp4 (16.2 MB)
    • 7. Save and Load model.srt (4.3 KB)
    4. Other Models
    • 1. Decision Tree.mp4 (33.1 MB)
    • 1. Decision Tree.srt (8.4 KB)
    • 2. Support Vector Machine.mp4 (23.5 MB)
    • 2. Support Vector Machine.srt (4.8 KB)
    • 3. Random Forest.mp4 (26.5 MB)
    • 3. Random Forest.srt (6.6 KB)
    • 4. K-Fold Cross Validation.mp4 (64.0 MB)
    • 4. K-Fold Cross Validation.srt (11.4 KB)
    • 5. Naves-Bayes 1.mp4 (28.9 MB)
    • 5. Naves-Bayes 1.srt (6.3 KB)
    • 6. Naves-Bayes 2.mp4 (32.3 MB)
    • 6. Naves-Bayes 2.srt (5.8 KB)
    • 7. Ensemble Learning.mp4 (37.1 MB)
    • 7. Ensemble Learning.srt (8.3 KB)
    • 8. L1 and L2.mp4 (21.6 MB)
    • 8. L1 and L2.srt (5.6 KB)
    5. Unsupervised Learning
    • 1. K-Means Clustering.mp4 (28.7 MB)
    • 1. K-Means Clustering.srt (8.5 KB)
    • 10. Data Cleaning.mp4 (55.9 MB)
    • 10. Data Cleaning.srt (8.7 KB)
    • 11. Feature Engineering.mp4 (33.5 MB)
    • 11. Feature Engineering.srt (4.6 KB)
    • 12. Applying the model.mp4 (23.0 MB)
    • 12. Applying the model.srt (3.0 KB)
    • 2. Intro to Deep Learning.mp4 (4.1 MB)
    • 2. Intro to Deep Learning.srt (1.8 KB)
    • 3. How to install Tensorflow.mp4 (9.2 MB)
    • 3. How to install Tensorflow.srt (2.6 KB)
    • 4. Matrix.mp4 (20.3 MB)
    • 4. Matrix.srt (5.6 KB)
    • 5. Customer Churn Prediction.mp4 (62.2 MB)
    • 5. Customer Churn Prediction.srt (13.5 KB)
    • 6. Precision,Recall,F1 Score.mp4 (15.7 MB)
    • 6. Precision,Recall,F1 Score.srt (4.5 KB)
    • 7. Data Cleaning.mp4 (90.9 MB)
    • 7. Data Cleaning.srt (18.2 KB)
    • 8. Apply the model.mp4 (38.8 MB)
    • 8. Apply the model.srt (6.7 KB)
    • 9. Introduction and Data Collection.mp4 (10.4 MB)
    • 9. Introduction and Data Collection.srt (3.1 KB)
    • Bonus Resources.txt (0.3 KB)

Code:

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