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Start your journey to become a
#DataScientist
Classroom Training
Job Guarantee
Internship
Fill applications for Data Science Immersive Bootcamp #gurgaon: https://bit.ly/2v7tMvZ pic.twitter.com/8bt6ySIzoP
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Dealing with a big dataset? You might want to give Spark SQL a try! This excellent hands-on tutorial by Lakshay Arora covers everything you need to know about this topic (including code!).
#BigData#Python#Spark#SQL https://buff.ly/2OLUy4f pic.twitter.com/GWmetT0nfF
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How to Get Started with
#NLP – 6 Unique Methods to Perform#Tokenization https://buff.ly/2B3xAht pic.twitter.com/iQ8qoJz2OX
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DougFoo provides this easy guide for hopping on the
#AutoML train using#MicrosoftAzure. This not includes steps for using the Visual#GUI, but also how to deploy your#MachineLearning model with only a few lines of#code! https://buff.ly/36PwPYd pic.twitter.com/hN67Z6rCDo
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In this article, we will walk through the steps of building a German-to-English language translation model using
#Keras. We’ll also take a quick look at the history of#machinetranslation systems with the benefit of hindsight. https://buff.ly/2RBqw1H pic.twitter.com/t0wBo7xnty
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Can you join/merge two or more
#dataframes in#Python? It's a question a lot of aspiring#DataScientists trip on! Excellent explanation by Gyan Tripathi! https://buff.ly/2ujFN1l pic.twitter.com/wBpApKlL8g
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An informative
#article for your read on 'Curb Your Enthusiasm or Seinfeld? Building a Naive Bayes Classifier with Scikit-Learn for#NaturalLanguageProcessing' by Alex Mitrani.#NLP#DataScience#Data https://buff.ly/2B3UntN pic.twitter.com/VUh4qJRcwN
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#avhackoftheday Do you know how you can get the history of all the commands running inside your#jupyter notebook? Use %history, jupyter notebook's built-in magic function! Note - Even if you have cut the cells in your notebook, %history will print those#commands as well!pic.twitter.com/Xmp5Zbo4kPHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
SQL Cheatsheet for every AI & ML aspirant
Become an AI & ML BlackBelt Professional - with this program (10+ courses) which develops combined expertise in #DataScience,#MachineLearning,#DeepLearning and tools such as#SQL.
Reserve your seat: https://bit.ly/2vPh8SF pic.twitter.com/2ttG0l1zI3
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A really interesting and relevant
#tutorial by Aarshay Jain for every#DataScientist He addresses one key component of designing an offline#evaluation environment - creating a test set to evaluate#MachineLearning performance. https://buff.ly/37XoKAU pic.twitter.com/GnWrvLK1UP
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Knowing
#MachineLearning algorithms is one part of an end-to-end#DataScience project. In this excellent article, Om Deskmukh talks about 4 key aspects, apart from building models, that are key to a successful DS#project. https://buff.ly/32EDbXh pic.twitter.com/elPs0KtCKU
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#TimeSeries Forecasting is a popular project for DS enthusiasts. However, Sarit Maitra goes one step further and adds technical indicators common among traders to the data. Learn#featureengineering techniques required for this along with#Python code. https://buff.ly/2Qsgnqt pic.twitter.com/1gTiyaGyBC
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Learn how to build a text summarization model using
#DeepLearning in#Python in this article by Aravind Pai. We will work on a really cool dataset of Amazon food reviews to understand and code our very own text#summarization model! https://buff.ly/2WZhrGu pic.twitter.com/SDUbJsttND
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Bayes theorem forms the backbone of one of very frequently used
#classification algorithms in#DataScience – Naive Bayes. Interesting article by Dishashree which introduces conditional#probability and#Bayestheorem using examples & real-life scenarios. https://buff.ly/2EZE17S pic.twitter.com/8lAAhtefjG
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#avhackoftheday Convert wide form dataframe into long form dataframe in just 1 line of code! In pd.melt(), one more columns are used as identifiers. "Unmelt the data", use pivot() functionpic.twitter.com/c44NWihTjGHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
With
#IPL2020 just a few days away, check out this amazing batting analysis for T20#cricket by Prateek Joshi. This covers the topic of Network Analysis on IPL 2019 batting partnerships.#MachineLearning#NetworkAnalysis https://buff.ly/2RSBzXo pic.twitter.com/UJEp7sSiR4
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Ever thought of "tuning up" yourself for enhancing performance as a
#DataScientist? There are various things, other than analytical tools &#languages that contribute a lot. What are they? Read here. https://buff.ly/2HKrJ74#Analyticspic.twitter.com/Tx5QRCWzje
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Must watch
#documentaries on#statistics and#MachineLearning which shows the rising importance of#data and#robotic devices. https://buff.ly/2RvCfOV pic.twitter.com/8GNUwyHShp
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Explore an alternative method of interpreting
#MachineLearning models which stems out of the#gametheory discipline. In this article, we will also introduce and talk about#ShapleyValues for#machinelearning interpretability. https://buff.ly/2MnVfzm pic.twitter.com/KdSQUrx8P5
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Do you find it tough to crack
#DataScience interviews? This amazing#course on ""Ace Data Science Interviews" covers different kinds of interviews in data science industry, steps to follow ace interviews & provides an#interview book with 240+ questions! https://buff.ly/38ZPIb9 pic.twitter.com/K01q8C0ncf
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