@DeepLearning_AI channel is moved to ๐๐๐
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Connect our channel and enjoy latest AI news, courses, books, source codes and so on..
channel description are given below:
Join us: @MachineLearning_DeepLearning_ai
Channel for who have a passion for -
* Artificial Intelligence
* Machine Learning
* Deep Learning
* Data Science
* Computer vision
* Image Processing
* Research Papers
* Related Courses and Ebooks
Join us: https://t.me/MachineLearning_DeepLearning_ai
Connect our channel and enjoy latest AI news, courses, books, source codes and so on..
channel description are given below:
Join us: @MachineLearning_DeepLearning_ai
Channel for who have a passion for -
* Artificial Intelligence
* Machine Learning
* Deep Learning
* Data Science
* Computer vision
* Image Processing
* Research Papers
* Related Courses and Ebooks
Here's 7 statistical & machine learning concepts that you should know for #DataScience:
Join: https://t.me/ComputerScience_MachineLearning
Join: https://t.me/DeepLearning_ai
Join: https://www.facebook.com/groups/MachineLearningSource/
1. Tree Based Methods
a. Decision Trees - https://lnkd.in/gBtCk9G
b. Random Forest - https://lnkd.in/g9FkczK
c. Gradient Boosting Trees - https://lnkd.in/gFPFGsk
2. Linear (Regularized) Models
a. Lasso & Ridge - https://lnkd.in/g3dJT-g
b. Linear Regression - https://lnkd.in/g7AS6Ar
c. Logistic Regression - https://lnkd.in/gq4EyJc
3. Hypothesis Testing & confidence
a. A/B Testing - https://lnkd.in/gmeijHV
b. Chi Square Test - https://lnkd.in/gG6vz2T
c. Statistical Tests - https://lnkd.in/gJcfTsq
4. Resampling Methods
a. Bootstrapping and Bagging - https://lnkd.in/gPmm4by
b. Cross Validation - https://lnkd.in/gsfsE6y
5. Clustering K-means
https://lnkd.in/gvNsp8N
6. Feature Selection
https://lnkd.in/gdCBWpB
7. Evaluation Metrics
a. Classification Metrics - https://lnkd.in/gxeyC6n
b. Regression Metrics - https://lnkd.in/gj4Eg9p
Join: https://t.me/ComputerScience_MachineLearning
Join: https://t.me/DeepLearning_ai
Join: https://www.facebook.com/groups/MachineLearningSource/
1. Tree Based Methods
a. Decision Trees - https://lnkd.in/gBtCk9G
b. Random Forest - https://lnkd.in/g9FkczK
c. Gradient Boosting Trees - https://lnkd.in/gFPFGsk
2. Linear (Regularized) Models
a. Lasso & Ridge - https://lnkd.in/g3dJT-g
b. Linear Regression - https://lnkd.in/g7AS6Ar
c. Logistic Regression - https://lnkd.in/gq4EyJc
3. Hypothesis Testing & confidence
a. A/B Testing - https://lnkd.in/gmeijHV
b. Chi Square Test - https://lnkd.in/gG6vz2T
c. Statistical Tests - https://lnkd.in/gJcfTsq
4. Resampling Methods
a. Bootstrapping and Bagging - https://lnkd.in/gPmm4by
b. Cross Validation - https://lnkd.in/gsfsE6y
5. Clustering K-means
https://lnkd.in/gvNsp8N
6. Feature Selection
https://lnkd.in/gdCBWpB
7. Evaluation Metrics
a. Classification Metrics - https://lnkd.in/gxeyC6n
b. Regression Metrics - https://lnkd.in/gj4Eg9p