#100dayslearningmachinelearning search results
Day20: Classify THIS , Stochastic Gradient Descent (SGD) Classifier #100DaysLearningMachineLearning @CloudxLab #python
Day20: Classy : Arbitrary power of ten score reached #100DaysLearningMachineLearning @CloudxLab #python
Day20: Moved onto multi-OUTPUT and suddenly got a whole lot NOISY in here -> incidentally "⚡️" is act of ME using python #100DaysLearningMachineLearning @CloudxLab #python
Day22: That feeling when the online training course is over, but there's so much more to learn #100DaysLearningMachineLearning @CloudxLab #python
Day20: Dare I digress away from regress #machine learning #100DaysLearningMachineLearning @CloudxLab #python
Day21: Computation complexity of decision tree is 🌳🌳🌳O(log_2(m)) 🌳🌳🌳#100DaysLearningMachineLearning @CloudxLab #python
Day19: Great use of an online environment to work step by step through the stages of this end-to-end project - training wheels are ON #100DaysLearningMachineLearning @CloudxLab #python
Day21: Green thumbs up all round as I go into decision trees today. Decision Trees= white box model, Random Forest = black box model #100DaysLearningMachineLearning @CloudxLab #python
Day23: Is it just me, or does Jupyter internalise errors? Code running in Jupyter took unexpect. long too run. Turned back to Spyder to discover code errors. Only after using targeted print statements do I see rpt of err in Jupyter #100DaysLearningMachineLearning #python
Day20: Classy : F1 score is the HARMONIC mean of recall and precision #thingsididnotknow #100DaysLearningMachineLearning @CloudxLab #python
Day23: Digging up old code and I am playing for my neglect with new, previously unthrown errors. Guess my code missed me. Perhaps even the equivalent of a pet chewing on my favourite slippers and tearing at the wallpaper. #feeloved #100DaysLearningMachineLearning #python
Day22: Rejigging code (again). Deciding between numpy and pandas . I like the tidyness of the pandas, but the extra formatting equates to extra overheads, which are not balanced out unless you have 50k-500k data #phd #100DaysLearningMachineLearning #python
Day20: @sandeepgiri Is your use of 42 as the seed for random number generators a reference to the answer to life, the universe and everything? np.random.seed(42) #randomquestion #100DaysLearningMachineLearning @CloudxLab #python
ICYMI: considered the "Hello World" for Machine Learning #thingsididnotknow #100DaysLearningMachineLearning @CloudxLab
ICYMI: considered a baseline data set for testing model performance #thingsididnotknow #100DaysLearningMachineLearning @CloudxLab
Day20: Multi_LABEL Classifiers sussed this out as being "odd" and not "large" => [True, False] #100DaysLearningMachineLearning @CloudxLab #python
Day20: Classify THIS , Stochastic Gradient Descent (SGD) Classifier #100DaysLearningMachineLearning @CloudxLab #python
Day22: Discovering new ways how my work and study lives are colliding. Check out the AI for drawing in @google quickdraw.withgoogle.com #100DaysLearningMachineLearning . Tossing up whether I could use it for supporting students' development of technical drafting skills
Day23: Is it just me, or does Jupyter internalise errors? Code running in Jupyter took unexpect. long too run. Turned back to Spyder to discover code errors. Only after using targeted print statements do I see rpt of err in Jupyter #100DaysLearningMachineLearning #python
Day23: Digging up old code and I am playing for my neglect with new, previously unthrown errors. Guess my code missed me. Perhaps even the equivalent of a pet chewing on my favourite slippers and tearing at the wallpaper. #feeloved #100DaysLearningMachineLearning #python
Day22: Discovering new ways how my work and study lives are colliding. Check out the AI for drawing in @google quickdraw.withgoogle.com #100DaysLearningMachineLearning . Tossing up whether I could use it for supporting students' development of technical drafting skills
Day22: Rejigging code (again). Deciding between numpy and pandas . I like the tidyness of the pandas, but the extra formatting equates to extra overheads, which are not balanced out unless you have 50k-500k data #phd #100DaysLearningMachineLearning #python
Day22: That feeling when the online training course is over, but there's so much more to learn #100DaysLearningMachineLearning @CloudxLab #python
Day21: Computation complexity of decision tree is 🌳🌳🌳O(log_2(m)) 🌳🌳🌳#100DaysLearningMachineLearning @CloudxLab #python
Day21: Green thumbs up all round as I go into decision trees today. Decision Trees= white box model, Random Forest = black box model #100DaysLearningMachineLearning @CloudxLab #python
Day20: Classy : Arbitrary power of ten score reached #100DaysLearningMachineLearning @CloudxLab #python
Day20: Classy : F1 score is the HARMONIC mean of recall and precision #thingsididnotknow #100DaysLearningMachineLearning @CloudxLab #python
Day20: Multi_LABEL Classifiers sussed this out as being "odd" and not "large" => [True, False] #100DaysLearningMachineLearning @CloudxLab #python
Day20: Classify THIS , Stochastic Gradient Descent (SGD) Classifier #100DaysLearningMachineLearning @CloudxLab #python
Day20: Moved onto multi-OUTPUT and suddenly got a whole lot NOISY in here -> incidentally "⚡️" is act of ME using python #100DaysLearningMachineLearning @CloudxLab #python
Day20: Classify THIS , Stochastic Gradient Descent (SGD) Classifier #100DaysLearningMachineLearning @CloudxLab #python
Day20: @sandeepgiri Is your use of 42 as the seed for random number generators a reference to the answer to life, the universe and everything? np.random.seed(42) #randomquestion #100DaysLearningMachineLearning @CloudxLab #python
ICYMI: considered a baseline data set for testing model performance #thingsididnotknow #100DaysLearningMachineLearning @CloudxLab
ICYMI: considered the "Hello World" for Machine Learning #thingsididnotknow #100DaysLearningMachineLearning @CloudxLab
Day20: Dare I digress away from regress #machine learning #100DaysLearningMachineLearning @CloudxLab #python
Day19: Great use of an online environment to work step by step through the stages of this end-to-end project - training wheels are ON #100DaysLearningMachineLearning @CloudxLab #python
Day20: Classy : Arbitrary power of ten score reached #100DaysLearningMachineLearning @CloudxLab #python
Day20: Classify THIS , Stochastic Gradient Descent (SGD) Classifier #100DaysLearningMachineLearning @CloudxLab #python
Day19: Rental Bike Hourly Demand End 2 End Project Assessment #100DaysLearningMachineLearning @CloudxLab #python
Day16: Gauss what? Passed through the density curves' End to End Project #100DaysLearningMachineLearning @CloudxLab #python
Day15: No chance of getting bit by pandas tonight 🐼🐼🐼🐼🐼🐼🐼🐼🐼🐼🐼🐼🐼🐼🐼 while I safari through mtcars.csv data 🔦🔦🔦🔦🔦🔦🔦🔦🔦🔦🔦🔦🔦🔦🔦 #100DaysLearningMachineLearning @CloudxLab #python
Day20: Dare I digress away from regress #machine learning #100DaysLearningMachineLearning @CloudxLab #python
Day13: tfw you have been supervised through a supervised machine learning project, and you are feeling a WHOLE lot like a learning machine. 🤖🤖🤖🤖🤖🤖 #100DaysLearningMachineLearning @CloudxLab #python
Day08: Levelling up the power of the scatterplot to investigate #data by including an #alpha transparency argument to further demonstrate clustering of points #100DaysLearningMachineLearning @CloudxLab #python 👩💻👉🧙♀️
Day08: The magic of transparency values, point sizing, and heatmaps when applied to a scatterplot #100DaysLearningMachineLearning @CloudxLab #python 👩💻👉🧙♀️
Day20: Moved onto multi-OUTPUT and suddenly got a whole lot NOISY in here -> incidentally "⚡️" is act of ME using python #100DaysLearningMachineLearning @CloudxLab #python
Day09: And what metrics do we start with #scatterplots ? Correlation coefficient and coefficient of determination. Feel pangs of regret over always focussing on first row, but not the others. R, I was blind, but now I see. #100DaysLearningMachineLearning @CloudxLab #python 🧙♀️
Goin' fishin' through course specifications and putting my machine learning into practice in #highered context. #100DaysLearningMachineLearning @CloudxLab #python
Day22: That feeling when the online training course is over, but there's so much more to learn #100DaysLearningMachineLearning @CloudxLab #python
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