#mlcourse_open - Twitter Hashtag

over 8 years ago

. https://t.co/yUerKaOW8o #mlcourse_open https://t.co/zOT0iheQA8

tumikosha's tweet photo. . https://t.co/yUerKaOW8o #mlcourse_open https://t.co/rqaQL0N3Sg https://t.co/zOT0iheQA8

over 8 years ago

Topic 9 of the Open Machine Learning Course by OpenDataScience @odsai_en covers time series analysis with Python. https://t.co/riq6mxJCYJ #mlcourse_open

ykashnitsky's tweet photo. Topic 9 of the Open Machine Learning Course by OpenDataScience @odsai_en covers time series analysis with Python. https://t.co/riq6mxJCYJ #mlcourse_open https://t.co/A8NtbD4mUC

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Yury Kashnitsky @ykashnitsky

over 8 years ago

Topic 9 of the Open Machine Learning Course by OpenDataScience @odsai_en covers time series analysis with Python. https://t.co/riq6mxJCYJ #mlcourse_open

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Yury Kashnitsky @ykashnitsky

over 8 years ago

Topic 8 of the Open Machine Learning Course by OpenDataScience @odsai_en covers Vowpal Wabbit and the reasons of its blazingly fast speed (Stochastic Gradient Descent and feature hashing) https://t.co/7i4hIemnc6 #mlcourse_open

ykashnitsky's tweet photo. Topic 8 of the Open Machine Learning Course by OpenDataScience @odsai_en covers Vowpal Wabbit and the reasons of its blazingly fast speed (Stochastic Gradient Descent and feature hashing) https://t.co/7i4hIemnc6 #mlcourse_open https://t.co/pb6fxFoknY

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Yury Kashnitsky @ykashnitsky

over 8 years ago

Topic 7 of the Open Machine Learning Course by @odsai_en and @libfun_sk is dedicated to unsupervised learning, namely, to Principal Component Analysis and clustering. https://t.co/N2UV6Lc9tw #mlcourse_open (credit for image to CS231n)

ykashnitsky's tweet photo. Topic 7 of the Open Machine Learning Course by @odsai_en and @libfun_sk is dedicated to unsupervised learning, namely, to Principal Component Analysis and clustering. https://t.co/N2UV6Lc9tw #mlcourse_open (credit for image to CS231n) https://t.co/nU40VEBDSP

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Yury Kashnitsky @ykashnitsky

over 8 years ago

Topic 6 of the Open Machine Learning Course is all about features: feature extraction, engineering, selection and transformation. There is less math here but these things make ML work better in practice. https://t.co/fceH9SAtsm by @arseny_info #mlcourse_open

ykashnitsky's tweet photo. Topic 6 of the Open Machine Learning Course is all about features: feature extraction, engineering, selection and transformation. There is less math here but these things make ML work better in practice. https://t.co/fceH9SAtsm by @arseny_info #mlcourse_open https://t.co/G72jKc14oy

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Yury Kashnitsky @ykashnitsky

over 8 years ago

Topic 5 of the Open Machine Learning Course is mostly about Random Forests, the model of first choice in lots of ML applications. In the assignment, you'll have a chance to compare RF to logistic regression in a credit scoring task. https://t.co/UNvCvHjxt6 #mlcourse_open

ykashnitsky's tweet photo. Topic 5 of the Open Machine Learning Course is mostly about Random Forests, the model of first choice in lots of ML applications. In the assignment, you'll have a chance to compare RF to logistic regression in a credit scoring task. https://t.co/UNvCvHjxt6 #mlcourse_open https://t.co/6mFl6i92dS

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Yury Kashnitsky @ykashnitsky

over 8 years ago

Topic 4 of the Open Machine Learning Course covers the most important material – linear models. Lots of math and practice, you'll beat a couple of benchmarks in a cool Kaggle Inclass competition https://t.co/0InIwXBkER #mlcourse_open

ykashnitsky's tweet photo. Topic 4 of the Open Machine Learning Course covers the most important material – linear models. Lots of math and practice, you'll beat a couple of benchmarks in a cool Kaggle Inclass competition https://t.co/0InIwXBkER #mlcourse_open https://t.co/u1arudNcN4

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