Jemput Pekerja Bebas ke Projek
Anda tidak mempunyai projek aktif pada masa ini. Kenapa tidak memaparkan projek sekarang? Ia percuma!Siarkan Projek
- 100%Kerja Diselesai
- 100%Mengikut Bajet
- 83%Tepat Pada Masa
- N/AKadar Ulang Upah
Project for Kartikeya K.
“Great and Knowledgeable Data Scientist”gregfmarschall 2 bulan lepas
R programming help
“Great programmer. I would highly recommend him to anyone and I will definitely use his services again!”twice2x 2 bulan lepas
Project for kartikeyakirar
“Has a lot of patience. Invested a lot of effort.”VoidBox 10 bulan lepas
crime analytics through social media data( news feeds)
“He is hardworking [login to view URL] me step by step to understand of project code.I enjoyed discussion with him.I would like to hire him again for post project works on the same domain.”brprathap9 11 bulan lepas
Simple R Plotly predict with a classifier(neural network) and sample data (need it to learn R)
“Very good freelancer. Helped me step by step doing a time series analysis in R. I recommend him for future projects.”kkopmetjespam 11 bulan lepas
Text Mining and Data Visualisation Research Project
“It took some time to start, but Kartikeya proved to be hard-working, knowledgeable, communicative, and invested, I very much enjoyed the experience and would hire him again. Recommended!”qhb16193 1 tahun lepas
Machine Learning Online Course Statement of Accomplishment (2015)COURSERA INC.
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Course contains introductory algorithms and deep knowledge regarding topic.
R Programming (2015)COURSERA INC.
In this course you will learn how to program in R and how to use R for effective data analysis. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
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