Top 20 #Python libraries for #DataScience in 2018

💡 What is a p-value?

When testing an hypothesis, the p-value is the likelihood that we would observe results at least as extreme as our result due purely to random chance if the null hypothesis were true.

💡 What does it mean when a p-value is low?

When the p-value is low, it is relatively rare for the our results to be purely from random variations in observations.

Because of this, we may decide to reject the null hypothesis. If the p-value is below some pre-defined threshold, we say that the result is "statistically significant" and we reject the null hypothesis.

💡 What value is most often used to determine statistical significance?

A value of alpha = 0.05 is most often used as the threshold for statistical significance.

#datascience #statistics

✴️ @AI_Python_EN

What are the best resources to learn major libraries for #DataScience in #Python. Here is my updated full list.
Will recommend to use Jupyter-Spyder environment to practice all these.

#DataLoading and #DataManipulation

✔️Numpy - https://bit.ly/1OLtuIF
✔️Scipy - https://bit.ly/2f3pitB
✔️Pandas - https://bit.ly/2qs1lAJ

#DataVisualization
✔️Matplotlib https://bit.ly/2gxxViI
✔️Seaborn https://bit.ly/2ABypQC
✔️Plotly https://bit.ly/2uJwULB
✔️Bokeh https://bit.ly/2uOFbxQ

#ML #DL #ModelEvaluation
✔️Scikit-Learn - https://bit.ly/2uYFNkw
✔️H20 - https://bit.ly/2M0hJnG
✔️Xgboost - https://bit.ly/2M3Vdut
✔️Tensorflow - https://bit.ly/2vfI5es
✔️Caffe- https://bit.ly/2a05bgt
✔️Keras - https://bit.ly/2vfDyZj
✔️Pytorch - https://bit.ly/2uXWY5U
✔️Theano - https://bit.ly/2v3N805


#analytics #artificialintelligence #machinelearning
#recommend

✴️ @AI_Python_EN

XGBoost: An Intuitive Explanation
Ashutosh Nayak : https://towardsdatascience.com/xgboost-an-intuitive-explanation-88eb32a48eff
#MachineLearning #DataScience #RandomForest #Xgboost #DecisionTree

توضیحاتی در مورد الگوریتم
Random Forest


https://www.instagram.com/p/B9HaR7ggeky/?igshid=1l3vvn7ybepp7

🤖⚡️ scikit-learn tip :
GridSearchCV taking too long? Try RandomizedSearchCV with a small number of iterations.

Make sure to specify a distribution (instead of a list of values) for continuous parameters!


#sklearntips #MachineLearning #Python #DataScience

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