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Like Mengz
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Registrace 30. 05. 2018
Make learning fun and effective!
Video
Xgboost model prediction on iris data: 100% accuracy
zhlédnutí 458Před rokem
Xgboost model prediction on iris data: 100% accuracy
Multi-class predictions: naive Bayes model on iris data
zhlédnutí 98Před rokem
Multi-class predictions: naive Bayes model on iris data
Master keywords in 90 seconds: on the way to pro!
zhlédnutí 45Před rokem
Master keywords in 90 seconds: on the way to pro!
Tidymodels in R: run LDA prediction on iris
zhlédnutí 104Před rokem
Tidymodels in R: run LDA prediction on iris
Apply LDA to iris data for multi-class predictions.
zhlédnutí 86Před rokem
Apply LDA to iris data for multi-class predictions.
Difference between shallow copy and deep copy in python
zhlédnutí 37Před rokem
Difference between shallow copy and deep copy in python
Fed is the boss, the stock markets follows.
zhlédnutí 43Před rokem
Fed is the boss, the stock markets follows.
Why Intel stock (INTC) is falling hard?
zhlédnutí 130Před rokem
Why Intel stock (INTC) is falling hard?
What is a recursive function ? How to use it?
zhlédnutí 13Před rokem
What is a recursive function ? How to use it?
How to plot a Normal Distribution in Python
zhlédnutí 78Před rokem
How to plot a Normal Distribution in Python
How to plot "Beta Distribution" in Python
zhlédnutí 1KPřed rokem
How to plot "Beta Distribution" in Python
Can consumer sentiment index help understand stock prices ?
zhlédnutí 41Před rokem
Can consumer sentiment index help understand stock prices ?
Proportion sampling from 11 sectors in S&P 500 stocks: 'rebound'?
zhlédnutí 22Před 2 lety
Proportion sampling from 11 sectors in S&P 500 stocks: 'rebound'?
China Stocks Rebound? EV and Solar, more than 60% YTD in Solar !
zhlédnutí 27Před 2 lety
China Stocks Rebound? EV and Solar, more than 60% YTD in Solar !
Bitcoin price dropped below $20,000, is it still too risky ?
zhlédnutí 28Před 2 lety
Bitcoin price dropped below $20,000, is it still too risky ?
Are Marijuana ETFs still trending down ?
zhlédnutí 16Před 2 lety
Are Marijuana ETFs still trending down ?
Any winners in ETFs ? sector by sector ?
zhlédnutí 23Před 2 lety
Any winners in ETFs ? sector by sector ?
Sampling from S&P500 stocks in Rstudio
zhlédnutí 276Před 2 lety
Sampling from S&P500 stocks in Rstudio
Sampling from S&P500 stocks : is the energy sector the new winner ?
zhlédnutí 17Před 2 lety
Sampling from S&P500 stocks : is the energy sector the new winner ?
A great book for data science and machine learning beginners !
zhlédnutí 42Před 2 lety
A great book for data science and machine learning beginners !
Five lines python: how to use filter() in python:
zhlédnutí 8Před 2 lety
Five lines python: how to use filter() in python:
Simple random sampling from S&P500 companies
zhlédnutí 29Před 2 lety
Simple random sampling from S&P500 companies
Web scraping S&P 500 companies table from wikipedia
zhlédnutí 110Před 2 lety
Web scraping S&P 500 companies table from wikipedia
U mean tech from the strongest battle ground from Roblox
Thanks for this video! I was totally stuck trying to complete Exercise 4.3 in "Computational Physics" by Mark Newman. Never having completed Calc 1, I was clueless. This helped me complete the exercise and post my solution to my question on stackoverflow in which I attributed the idea to your video. regards!~saucerdesigner
Glad it helped!
Nice programming
how would you add all of those scores up
define a counter, then sum all the numbers...within the loop...
Tips on using R, use python
use R in python: rpy2, while in R using python: reticulate! cheers.
The best tip for R is to not use it anymore because it is quickly dying over better alternatives.
If you use it, learn it, if not why bother? Everyone thought C or Java would die sooner or later, the fact is that neither did! Again, if you use it, learn it!
Are you doing this on mobile phone 📱? If 'yes' : please what's the name of the app Else: thanks for sharing
i am using macbook, screen recording, keep it about 8 x 12 (W x H) inches window, so it can fit a mobile/vertical screen. cheers
@@likemengz9446 oh great, in googling for answers i found out a way to use jupyter on Android with pydroid 3 it cool.
Nice and simple, well done!
Music?
*Promosm*
WHAT!
Love R for stats
Do you not have to shuffle the rows?
When the data partition is created, such as 75/25 for training/test data sets, it is 'randomly' sampled or shuffled. It's similar to 'use sample()'.
This is amazing. can u share the codes i could practice.
Sorry for late replying, here is the link: github.com/PyRPy/TraderZone/blob/master/StocksPred/SPY_ARIMA.Rmd I also added the link in the description. Many thanks.
What is the fpc? why do you use the rep function with it?
finite population correction; need to duplicate the corrections.
What is the preferred text book you recommend for sampling in R I should consider buying?
Sampling, 3rd Edition, Steven K. Thompson, would be a good one. Complex survey in R faculty.washington.edu/tlumley/old-svybook/index.html, would be helpful too.
@@likemengz9446 thankyou very much
PCA is an unsupervised exploratory analysis method. Using an unsupervised method like this and then trying to run a supervised logistic regression model will not yield reliable results. Try reducing dimensions using partial least squares or some other supervised method, then continue with the logistic regression!
Agree.
Sir your video quality needs to be improved. Edit: After 15 seconds its fine. Thank you.
Noted. Thanks.
hi thank you for the video, could you show us if that works in your machine? is it on windows?
Windows 10, for tensorflow in Rstudio, need to install python first.
Could you help: How can I assign the accuracy to a variable, like a=accuracy or a = binary_accuracy. This is part of the code of the neural network: model = Sequential() model.add(Dense(48, input_dim=48, activation='relu')) model.add(Dense(24, activation='relu')) model.add(Dense(2, activation='sigmoid')) model.compile(loss='mean_squared_error', optimizer='adam', metrics=['binary_accuracy']) model.fit(training_data, target_data, epochs=1000) scores = model.evaluate(training_data, target_data) "training_data, target_data are arrays" Result of evaluation: binary_accuracy: 0.5000 binary_accuracy: 50.00%
you could use : accuracy_score(), such as 'accuracy_score(y_test, y_pred)', and assign it to a variable. here is a template for your reference : github.com/PyRPy/ML_Py_Templates/blob/master/DataCamp_Templates_Py/Template_Scikit_Learning_Keras.ipynb Hope this would be helpful.
Thank you very much for your explanation. Greetings from Peru !!!
You are welcome!
code is here: github.com/PyRPy/stats_r/tree/master/ReticulatePy