Discover and read the best of Twitter Threads about #stat
Most recents (10)
But what p-value means in #MachineLearning - A thread
It tells you how likely it is that your data could have occurred under the null hypothesis
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#DataScience #DeepLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat
It tells you how likely it is that your data could have occurred under the null hypothesis
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#DataScience #DeepLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat
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What Is a Null Hypothesis?
A null hypothesis is a type of statistical hypothesis that proposes that no statistical significance exists in a set of given observations.
#DataScience #MachineLearning #100DaysOfMLCode #Python #stat #Statistics #Data #AI #Math #deeplearning
What Is a Null Hypothesis?
A null hypothesis is a type of statistical hypothesis that proposes that no statistical significance exists in a set of given observations.
#DataScience #MachineLearning #100DaysOfMLCode #Python #stat #Statistics #Data #AI #Math #deeplearning
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A P-value is the probability of obtaining an effect at least as extreme as the one in your sample data, assuming the truth of the null hypothesis
#DataScience #MachineLearning #100DaysOfMLCode #Python #DataScientist #Statistics #Data #DataAnalytics #AI #Math
A P-value is the probability of obtaining an effect at least as extreme as the one in your sample data, assuming the truth of the null hypothesis
#DataScience #MachineLearning #100DaysOfMLCode #Python #DataScientist #Statistics #Data #DataAnalytics #AI #Math
Did you know how TensorFlow can run on a single mobile device as well as on an entire data center? Read this thread
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#TensorFlow #DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data
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#TensorFlow #DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data
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Google has designed TensorFlow such that it is capable of dividing a large model graph whenever needed.
#TensorFlow #DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat #AI
Google has designed TensorFlow such that it is capable of dividing a large model graph whenever needed.
#TensorFlow #DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat #AI
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It assigns special SEND and RECV nodes whenever a graph is divided between multiple devices (CPUs or GPUs).
#TensorFlow #DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat #AI
It assigns special SEND and RECV nodes whenever a graph is divided between multiple devices (CPUs or GPUs).
#TensorFlow #DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat #AI
A thread on AUC Score (Area under the ROC Curve) Interpretation in #DataScience #MachineLearning
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#DeepLearning #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Math #Data #DataAnalytics #pythoncode #AI #ArtificialIntelligence #TensorFlow #PyTorch #Pandas
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#DeepLearning #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Math #Data #DataAnalytics #pythoncode #AI #ArtificialIntelligence #TensorFlow #PyTorch #Pandas
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"roc_auc_score" is defined as the area under the ROC curve, which is the curve having False Positive Rate on the x-axis and True Positive Rate on the y-axis at all classification thresholds.
#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python
"roc_auc_score" is defined as the area under the ROC curve, which is the curve having False Positive Rate on the x-axis and True Positive Rate on the y-axis at all classification thresholds.
#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python
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AUC ranges in value from 0 to 1.
#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Math #Data #DataAnalytics #pythoncode #AI #ArtificialIntelligence #TensorFlow #PyTorch #Pandas #Stat #dataviz #learning
AUC ranges in value from 0 to 1.
#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Math #Data #DataAnalytics #pythoncode #AI #ArtificialIntelligence #TensorFlow #PyTorch #Pandas #Stat #dataviz #learning
Outlier Detection with Alibi Detect Library - A Thread
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#DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat #pythoncode #AI #ArtificialIntelligence
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#DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat #pythoncode #AI #ArtificialIntelligence
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Alibi Detect is a Python library for detecting outliers, adversarial data, and drift. Accommodates tabular data, text, images, and time series that can be used both online and offline. Both TensorFlow and PyTorch backends are supported
#DataScience #DeepLearning
Alibi Detect is a Python library for detecting outliers, adversarial data, and drift. Accommodates tabular data, text, images, and time series that can be used both online and offline. Both TensorFlow and PyTorch backends are supported
#DataScience #DeepLearning
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Supports a variety of outlier detection techniques, including Mahalanobis distance, Isolation forest, and Seq2seq
#DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat #pythoncode
Supports a variety of outlier detection techniques, including Mahalanobis distance, Isolation forest, and Seq2seq
#DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat #pythoncode
What is p-value - A thread
It tells you how likely it is that your data could have occurred under the null hypothesis.
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#DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat
It tells you how likely it is that your data could have occurred under the null hypothesis.
1/n
#DataScience #DeepLearning #MachineLearning #ComputerVision #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Data #Math #Stat
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What Is a Null Hypothesis?
A null hypothesis is a type of statistical hypothesis that proposes that no statistical significance exists in a set of given observations.
#DataScience #MachineLearning #100DaysOfMLCode #Python #stat #Statistics #Data #AI #Math #deeplearning
What Is a Null Hypothesis?
A null hypothesis is a type of statistical hypothesis that proposes that no statistical significance exists in a set of given observations.
#DataScience #MachineLearning #100DaysOfMLCode #Python #stat #Statistics #Data #AI #Math #deeplearning
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A P-value is the probability of obtaining an effect at least as extreme as the one in your sample data, assuming the truth of the null hypothesis
#DataScience #MachineLearning #100DaysOfMLCode #Python #DataScientist #Statistics #Data #DataAnalytics #AI #Math
A P-value is the probability of obtaining an effect at least as extreme as the one in your sample data, assuming the truth of the null hypothesis
#DataScience #MachineLearning #100DaysOfMLCode #Python #DataScientist #Statistics #Data #DataAnalytics #AI #Math
A thread on AUC Score (Area under the ROC Curve) Interpretation in #DataScience #MachineLearning
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#DeepLearning #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Math #Data #DataAnalytics #pythoncode #AI #ArtificialIntelligence #TensorFlow #PyTorch #Pandas
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#DeepLearning #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Math #Data #DataAnalytics #pythoncode #AI #ArtificialIntelligence #TensorFlow #PyTorch #Pandas
2/16
"roc_auc_score" is defined as the area under the ROC curve, which is the curve having False Positive Rate on the x-axis and True Positive Rate on the y-axis at all classification thresholds.
#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python
"roc_auc_score" is defined as the area under the ROC curve, which is the curve having False Positive Rate on the x-axis and True Positive Rate on the y-axis at all classification thresholds.
#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python
3/16
AUC ranges in value from 0 to 1.
#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Math #Data #DataAnalytics #pythoncode #AI #ArtificialIntelligence #TensorFlow #PyTorch #Pandas #Stat #dataviz #learning
AUC ranges in value from 0 to 1.
#DataScience #MachineLearning #DeepLearning #100DaysOfMLCode #Python #DataScientist #Statistics #programming #Math #Data #DataAnalytics #pythoncode #AI #ArtificialIntelligence #TensorFlow #PyTorch #Pandas #Stat #dataviz #learning
SERÍA NUESTRA VACUNA?
“La vacuna Covid de #AstraZeneca ha estado marcada por nobles intenciones, errores de comunicación, juicios complicados, pesadillas de fabricación y rivalidad política y económica. ¿Cómo fue que todo salió tan mal?
trib.al/mktYhO9 vía @BW #Bloomberg
“La vacuna Covid de #AstraZeneca ha estado marcada por nobles intenciones, errores de comunicación, juicios complicados, pesadillas de fabricación y rivalidad política y económica. ¿Cómo fue que todo salió tan mal?
trib.al/mktYhO9 vía @BW #Bloomberg
“Mene Pangalos, jefe de investigación biofarmacéutica de #AstraZeneca Plc, se acostó el lunes 22 de marzo sintiéndose bien por primera vez en mucho tiempo. Después de trabajar las 24 hs del día durante el fin de semana, acababa de anunciar mejor que los resultados intermedios”.
“Eran resultados del gran ensayo de vacunación de la compañía en EEUU 🇺🇸: La inyección fue segura y 79% efectiva para prevenir casos de #Covid19 sintomático. Noticias positivas, por fin, después de meses de preguntas sobre todo, incluida la seguridad y la escasez de suministros”.
The first practice I was at in the US was a 2 doctor office. I worked in one half with 2 assistants and the other dentist in the other half.
One of my assistants had been in the business for over 30 years. She knew her s**t. When my colleague relocated, I asked the
One of my assistants had been in the business for over 30 years. She knew her s**t. When my colleague relocated, I asked the
office manager to have him assist the new guy because he was very fresh and inexperienced.
One day, I was in the middle of a tough root canal when she came running and said "Dr.G stat" and ran back.
I literally stopped what I was doing, told the assistant to stay with my
One day, I was in the middle of a tough root canal when she came running and said "Dr.G stat" and ran back.
I literally stopped what I was doing, told the assistant to stay with my
patient and ran over to the other side. One look at the patient and I knew he was having a heart attack.
I yelled out "911" which is the emergency helpline, asked them to say "suspected heart attack" which would get the paramedics on their way.
We got the patient on
I yelled out "911" which is the emergency helpline, asked them to say "suspected heart attack" which would get the paramedics on their way.
We got the patient on
[📂 THREAD]
Je vous propose un thread sur une équipe que je suis tout particulièrement depuis plusieurs saisons : 🇺🇸 @HBAxeon. Cette équipe, qui se concentre sur la formation des jeunes, a vu passer de grands noms du cyclisme.
Quelques noms détaillés 👇
Je vous propose un thread sur une équipe que je suis tout particulièrement depuis plusieurs saisons : 🇺🇸 @HBAxeon. Cette équipe, qui se concentre sur la formation des jeunes, a vu passer de grands noms du cyclisme.
Quelques noms détaillés 👇
@HBAxeon #Sponsoring 💶 / L'équipe américaine a été lancée par Lance Armstrong et de nombreux proches en 2009. Financée par Capital Sports & Entertainment (CSE), société dirigée par Bill Stapleton, elle prend le nom à l'époque Trek-Livestrong.
@HBAxeon Elle soulève rapidement un budget conséquent. Considérée comme satellite de Radioshack, elle partage les mêmes sponsors : Trek, Radioshack, Nissan et Bontrager. Ce qui permet dès la première année de signer notamment un grand espoir du cyclisme américain : 🇺🇸 Taylor Phinney.
#Research
#Stat
#Banknifty From Mar 2010 to Jan 2019
A) Open to Close abs %.
No. of trading days 2160
No. of days open to close > 1% = 750 (35%)
No. of days open to close > 2% = 247 (11.5%)
No. of days open to close > 3% = 58 (2.7%)
No. of days open to close > 4% = 13 (0.60%)
..
#Stat
#Banknifty From Mar 2010 to Jan 2019
A) Open to Close abs %.
No. of trading days 2160
No. of days open to close > 1% = 750 (35%)
No. of days open to close > 2% = 247 (11.5%)
No. of days open to close > 3% = 58 (2.7%)
No. of days open to close > 4% = 13 (0.60%)
..
......
No. of days open to close > 5% = 4 (0.20%)
No. of days open to close > 6% = 2 (0.09%)
No. of days open to close > 7% = 0 (0%)
% is absolute of + / -, ie can be either up or down.
So essentially at the minimum one should ideally trade only 35% of the times intraday...
No. of days open to close > 5% = 4 (0.20%)
No. of days open to close > 6% = 2 (0.09%)
No. of days open to close > 7% = 0 (0%)
% is absolute of + / -, ie can be either up or down.
So essentially at the minimum one should ideally trade only 35% of the times intraday...
.....
B) CPR width Vs Trend
During 1% move, ie 750 times, 38% times (288 dys) CPR width was < 0.68 times 20 day average; Out of 288 dys, 89% (255 dys), PDR was < 2%.
During 2% move, ie 247 times, 37% times (92 dys) CPR width was < 0.68 times 20 day average.
....
B) CPR width Vs Trend
During 1% move, ie 750 times, 38% times (288 dys) CPR width was < 0.68 times 20 day average; Out of 288 dys, 89% (255 dys), PDR was < 2%.
During 2% move, ie 247 times, 37% times (92 dys) CPR width was < 0.68 times 20 day average.
....
