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[DesireCourse.Net] Udemy - Machine Learning - A-Z™ Full Course

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File Name
Size
1. Introduction/1. Introduction.mp4
8.5 MB
1. Introduction/1. Introduction.vtt
723 B
1. Introduction/2. 1.html
3.6 kB
2. Machine Learning using R/1. Machine Learning Basics.mp4
92 MB
2. Machine Learning using R/1. Machine Learning Basics.vtt
19 kB
2. Machine Learning using R/10. Sentiment Analysis in R.mp4
403 MB
2. Machine Learning using R/10. Sentiment Analysis in R.vtt
61 kB
2. Machine Learning using R/11. Data Mining using R.mp4
299 MB
2. Machine Learning using R/11. Data Mining using R.vtt
45 kB
2. Machine Learning using R/12. Apriori Algorithm Explained Association Rule Mining Finding Frequent Itemset.mp4
102 MB
2. Machine Learning using R/12. Apriori Algorithm Explained Association Rule Mining Finding Frequent Itemset.vtt
21 kB
2. Machine Learning using R/13. Boosting Machine Learning.mp4
140 MB
2. Machine Learning using R/13. Boosting Machine Learning.vtt
27 kB
2. Machine Learning using R/13.1 (The Morgan Kaufmann series in machine learning).pdf.pdf
10 MB
2. Machine Learning using R/2. Data Science vs Machine Learning.mp4
127 MB
2. Machine Learning using R/2. Data Science vs Machine Learning.vtt
22 kB
2. Machine Learning using R/3. Machine Learning with R Machine.mp4
301 MB
2. Machine Learning using R/3. Machine Learning with R Machine.vtt
52 kB
2. Machine Learning using R/4. Complete Machine Learning Course.mp4
901 MB
2. Machine Learning using R/4. Complete Machine Learning Course.vtt
150 kB
2. Machine Learning using R/5. Machine Learning Algorithms.mp4
375 MB
2. Machine Learning using R/5. Machine Learning Algorithms.vtt
59 kB
2. Machine Learning using R/6. Linear Regression Algorithm.mp4
187 MB
2. Machine Learning using R/6. Linear Regression Algorithm.vtt
38 kB
2. Machine Learning using R/7. Linear Regression vs Logistic Regression.mp4
152 MB
2. Machine Learning using R/7. Linear Regression vs Logistic Regression.vtt
28 kB
2. Machine Learning using R/8. Random Forest Tutorial.mp4
515 MB
2. Machine Learning using R/9. Support Vector.mp4
221 MB
2. Machine Learning using R/9. Support Vector.vtt
40 kB
3. Machine Learning using Python/1. R vs Python.mp4
62 MB
3. Machine Learning using Python/1. R vs Python.vtt
8.8 kB
3. Machine Learning using Python/10. Q Learning Explained Reinforcement Learning.mp4
143 MB
3. Machine Learning using Python/10. Q Learning Explained Reinforcement Learning.vtt
35 kB
3. Machine Learning using Python/11. Probabilistic Graphical Models.mp4
203 MB
3. Machine Learning using Python/11. Probabilistic Graphical Models.vtt
40 kB
3. Machine Learning using Python/12. Machine Learning Projects.mp4
199 MB
3. Machine Learning using Python/12. Machine Learning Projects.vtt
37 kB
3. Machine Learning using Python/12.1 Olivier Bousquet, Ulrike von Luxburg, Gunnar Rätsch.pdf.pdf
5.1 MB
3. Machine Learning using Python/2. Logistic Regression in Python.mp4
365 MB
3. Machine Learning using Python/2. Logistic Regression in Python.vtt
73 kB
3. Machine Learning using Python/3. Decision Tree Algorithm.mp4
316 MB
3. Machine Learning using Python/3. Decision Tree Algorithm.vtt
64 kB
3. Machine Learning using Python/4. K Means Clustering Algorithm K Means Example in Python.mp4
202 MB
3. Machine Learning using Python/5. Naive Bayes Classifier in Python.mp4
198 MB
3. Machine Learning using Python/5. Naive Bayes Classifier in Python.vtt
37 kB
3. Machine Learning using Python/6. Time Series Analysis.mp4
270 MB
3. Machine Learning using Python/6. Time Series Analysis.vtt
57 kB
3. Machine Learning using Python/7. Twitter Sentiment Analysis.mp4
29 MB
3. Machine Learning using Python/7. Twitter Sentiment Analysis.vtt
5.1 kB
3. Machine Learning using Python/8. A Quick Guide To Sentiment Analysis.mp4
56 MB
3. Machine Learning using Python/8. A Quick Guide To Sentiment Analysis.vtt
10 kB
3. Machine Learning using Python/9. Reinforcement Learning.mp4
329 MB
3. Machine Learning using Python/9. Reinforcement Learning.vtt
68 kB
4. Projects in ML/1. First project Motion Studio.html
7.1 kB
4. Projects in ML/1.1 Adaptive Computation and Machine Learning.pdf.pdf
6.6 MB
4. Projects in ML/10. More ideas For projects.html
7.0 kB
4. Projects in ML/11. Top Projects for Bieng Expert.html
9.0 kB
4. Projects in ML/12. Projects For Practise.html
9.6 kB
4. Projects in ML/2. Lithion power.html
7.4 kB
4. Projects in ML/2.1 (Information science and statistics) Christopher M. Bishop - Pattern Recognition and Machine Learning-Springer (2006).pdf.pdf
4.5 MB
4. Projects in ML/2.1 Information science and statistics.pdf.pdf
4.5 MB
4. Projects in ML/3. BluEX.html
14 kB
4. Projects in ML/3.1 (Adaptive Computation and Machine Learning) Ethem Alpaydin - Introduction to Machine Learning -The MIT Press (2004).pdf.pdf
36 MB
4. Projects in ML/4. Forecasting Website Traffic Using Facebook’s Prophet Library.html
14 kB
4. Projects in ML/5. Face Recognition with Python.html
8.9 kB
4. Projects in ML/6. Digit Recognition.html
14 kB
4. Projects in ML/7. Predicting Google’s Stock Price.html
10 kB
4. Projects in ML/8. Predict the Weather.html
34 kB
4. Projects in ML/9. Speech Recognition.html
43 kB
[CourseClub.Me].url
48 B
[DesireCourse.Net].url
51 B