Building Next-Generation AI Professionals ๐ Unlocking knowledge, skills & opportunities through blogs, world-class courses, hackathons & a thriving community.
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We're excited to welcome Arun Prakash Asokan, Global Director of Data Science and AI at Novartis, to DataHack Summit 2026.
With nearly two decades of experience in AI and a track record of driving enterprise-scale AI adoption, Arun has been at the forefront of translating cutting-edge AI research into real business impact.
In his workshop, "When Agents Meet Graphs: The Rise of Knowledge-Driven GenAI," he will explore how knowledge graphs and agentic systems can move beyond traditional RAG to enable deeper reasoning, richer context, and more intelligent AI applications
If you're interested in the next evolution of GenAI systems, this workshop is not to be missed.
๐
Aug 05โ08 | Bengaluru | analyticsvidhya.com/datahackโฆ
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Visualizing Netflix Data Using Python: buff.ly/3nyxBDN
#Netflix #Python #DataScience #DataVisualization
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Which Data Science Job Role do you prefer?
โข ML Engineer
โข Data Analyst
โข Data Scientist
โข Other(Comment below)
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Letโs determine the outcome of the harvest season, i.e. whether the crop๐พ would be healthy (alive), damaged by pesticides๐งด, or damaged by other reasonsโ๏ธ, with the help of Machine Learning- buff.ly/3iT6UHC
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SQL is a language every data scientist must learn. Learn the basics of #SQL and #RDBMS in this simplified guide! buff.ly/2K9DRdY #BusinessIntelligence
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#Sklearn or scikit-learn is the most useful library for machine learning in #Python. Learn about different types of objects that are present in Sklearn and get a clear idea about the usecases of different functions in your #MachineLearning Pipeline - buff.ly/35gXZHY
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Andrew Ng's teachings on #machinelearning serve as a great introduction to the topic, but the only catch is it's done using #Octave. In this article, Srikar has used #Python to implement all the programming assignments. A very useful resource!
buff.ly/2C6Wct6
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MLR - one incredible package that includes all of the ML algorithms which we use frequently. Learn & practice how to use it in R, here. bit.ly/2D7CGJb #rstats #machinelearning
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Time to get introduced to the concepts of #SQL and #RDBMS - take this simplified guide and get your hands on this language! buff.ly/2m4Xytv #businessintelligence
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In order to become a complete #DataScientist it is essential to know the mathematics behind #MachineLearning. This article covers various mathematical aspects you need to know to become a machine learning master, incl. linear algebra, probability, and more buff.ly/3xY0z2w
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Evaluating a model is a core part of building an effective machine learning model. Learn different evaluation metrics, like confusion matrix, cross-validation, AUC-ROC curve, etc in this power-packed article: buff.ly/3mEA7YE
#Evaluation #MachineLearning #AnalyticsVidhya
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From cheatsheets, video links, e-books, research paper links & more, here're Top 25 Data Science & Machine Learning GitHub Repositories that you must lay your hands on and put them into action, right here! #cheatsheet #github #datascience #machinelearning buff.ly/2FRZK3D
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Are you looking to learn data science? What's a better way than applying your knowledge on a project?
Here's a list of 24 #DataScience projects that you need to try today to improve your skillset! #MachineLearning #DataScientist #DataAnalysis buff.ly/3oIilCl
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๐ข FREE Machine Learning Certification: buff.ly/3gYaeze
If you invest 8 โ 10 hours a week for this course, you can complete the entire course within 6 โ 8 weeks!
#machinelearning #course #beginner
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From cheatsheets, video links, e-books, research paper links & much more, here are the Top 25 (selected) Data Science and Machine Learning GitHub Repositories from 2018 - a must read!. buff.ly/2Q5AGa5
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How many time series techniques can you name? Here are 7 different methods to work with #TimeSeries data!
Get a detailed explanation of each approach along with code to implement all 7 methods in #Python.
#datascience #analytics #machinelearning
buff.ly/2ZrZdgH
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XGBoost is one of the popular #machinelearning algorithm used in #datascience competitions? buff.ly/2klDCDg
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Here are 25 Best #DataScience Projects on GitHub from 2018 that you, as a data scientist, must lay hands on and improvise your skills! Simply click on each project title to head over to the code repository on #GitHub. buff.ly/2Q5AGa5
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Andrew Ng's teachings on #machinelearning serve as a great introduction to the topic, but the only catch is it's done using #Octave. Srikar, in this article, has used #Python to implement all the programming assignments. A very useful resource!
buff.ly/2C6Wct6
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This elaborative article will let you explore #MonteCarlo learning, right from its basics. It's a slightly complex subject and well explained by Ankit, right here. He's then using the #OpenAI Gym toolkit in #Python to implement this method as well: buff.ly/2Exsk9A
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#avhackoftheday
Create bar plot over your pandas dataframe!
It'll give you a great yet simple overview of the data in just one line of code!
#python #pandas
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Free Courses in Data Science, Machine Learning & Deep Learning for everyone (Join here ๐ buff.ly/3h1bOi6)
#DataScience #MachineLearning #DeepLearning #COURSES
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Download this #cheatsheet which provides codes ( #Python and #R) for 10 machine learning #algorithms - and keep it handy while working on data sets! buff.ly/2GYAZlQ
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A useful guide for all beginners in machine learning & data science - It lists down the most active data scientist on #github, free #books, #ipython notebooks, tutorials on github. buff.ly/2te2vDW
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Which was the first Machine Learning model that you built? ๐ค
โข K-NN
โข Linear Regression
โข Decision Tree
โข Other (Comment Below)
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A useful guide for all beginners in #machinelearning & #DataScience - It lists down the most active data scientist on github, free #books, ipython notebooks, tutorials on github. buff.ly/2te2vDW
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Time to get introduced to the concepts of SQL and RDBMS - take this simplified guide and get your hands on this language! bit.ly/2EfBDYa #BusinessAnalytics #BusinessIntelligence
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Naive Bayes Algorithm simplified in 6 easy steps, with codes in #Python. Get started! buff.ly/2cKpjUf #machinelearning
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Naive Bayes Theorem is a best choice when you come across large data sets. These 6 steps, chalked out by Sunil, will get you started with it, pretty easily! buff.ly/2sqz55F #machinelearning #python #R
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Free Courses in Data Science, Machine Learning & Deep Learning for everyone (Join here ๐bit.ly/36DByMT)
#DataScience #MachineLearning
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Time to get introduced to the concepts of #SQL and RDBMS - take this simplified guide and get your hands on this language! (Author: Ajay Ohri) bit.ly/2Eisn5i #BusinessIntelligence
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โMachine Learning to Predict Taxi Fare โ Part One : Exploratory Analysisโ by Aiswarya Ramachandran medium.com/p/machine-learninโฆ
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#AVBytes UC Berkeley has open sourced the largest and most diverse self-driving dataset in the world. As a data scientist, this is something you should get your hands on NOW! & there are 3 challenges as well to test yourself against the best. buff.ly/2kKvOK6 #SelfDriving
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NumPy, Matplotlib, Seaborn and Pandas - powerful librariesย to perform data exploration in #Python. bit.ly/2F7EQde #datascience
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Understand the basics of Monte Carlo Learning - #algorithm used when there is no prior information of the environment & all information is essentially collected by experience. Weโll use the #OpenAI Gym toolkit in #Python to implement this method as well. buff.ly/2MCtu52
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Andrew Ng's teachings on #machinelearning serve as a great introduction to the topic, but the only catch is it's done using #Octave. In this article, Srikar has used #Python to implement all the programming assignments. A very useful resource!
buff.ly/2C6Wct6
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Time to get introduced to the concepts of #SQL and #RDBMS - take this simplified #guide and get your hands on this language! buff.ly/2RMKV3D
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How many #regression techniques are you aware of? Let's get to know these 7 types of techniques, here. buff.ly/2JO3PEv #Statistics #MachineLearning
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These 28 cheat sheets for #MachineLearning, Data science, Probability, SQL & #BigData will check the way you work! Bookmark them for your ready reference. (Author: Swati Kashyap) buff.ly/2rXm3vn
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Ramya Bhaskar has a perfect tutorial for you to explore #XGBoost, from its basics to advanced applications in details and deep dive into the inner workings of this powerful technique. Take a head start here. buff.ly/2S5fLpG #machinelearning
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Let's take a look at #XGBoost - the holy grail of #machinelearning hackathons. A comprehensive understanding of the algorithm to help you become better at machine learning. buff.ly/2CG8ZTR
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Time to get introduced to the concepts of #SQL and #RDBMS - take this simplified guide and get your hands on this language! buff.ly/2m4Xytv #BusinessIntelligence
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Here's an excellent resource with 24 different real time #projects for all #datascience professionals - beginners to advanced to test their skills! Once you complete a few projects, don't forget to showcase them on your resume and your #GitHub profile. buff.ly/2WWOqs6
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You need to keep practicing on projects to build up skills and boost your knowledge. Start working on these problems/datasets from different domains suitable for beginners, intermediate & advanced professionals. #MachineLearning #Python buff.ly/2kF47Cy
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Compilation of various #machinelearning algorithms, along with their #R & #Python codes. So, if you are looking to equip yourself to start building machine learning project - this is what you should lay your hands onto! buff.ly/2Kt7Oq2
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PCA is a method of extracting important variables from a large set of variables available in a data set. A practical guide to learn about #PrincipalComponentAnalysis in most simplified way alongwith its implementation in #Python and #R. buff.ly/2DGlUmw
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This is one of the best guides to get an understanding about the most commonly used #MachineLearning algorithms. Sunil Ray has even provided codes in #Python and #R for each technique. A must-read!
buff.ly/2FS08iB
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Dimensionality reduction is a popular #machinelearning topic, but how many techniques are you aware of? This brilliant article covers 12 techniques, with their implementation in #Python, that will make you a master of this subject! buff.ly/2Wxu3kQ
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Let's get started with #Altair - a very user-friendly #visualization library in #Python which actually performs a lot of things with the minimal amount of code - an introduction by Shubham Jain. buff.ly/2FL71kd
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Providing you with cheatsheets for Scikit-learn and Caret the most widely used machine library in #Python & R respectively by Kunal Jain. This is going to be a handsome resource for any Python or R practitioner. Download the Pdf files now. bit.ly/2CZTbqP #machinelearning
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Here is a package which includes all #machinelearning algorithms we use frequently! #MLR is absolutely incredible at performing machine learning tasks. Let's try improving accuracy of a classification problem using machine learning and explore. buff.ly/2mj8vYI #R
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Highly recommended e-books (available for free) on #MachineLearning that you must go through, in order to explore the underlying concepts of #statistics, #datascience #machinelearning ! buff.ly/2LseMwd #books
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Join this free course on #Scikitlearn >>> buff.ly/3dXbzCU and learn:
1. Scikit-learn in Python
2. Use of scikit-learn in Data Science Cycle
3. Use of scikit-learn in Model Building
4. Machine Learning Pipeline using scikit-learn
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Here's a comprehensive article to let you explore concepts of #DeepLearning & Neural networks right from basics. buff.ly/2sUaeGN #MachineLearning
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A useful guide for all beginners in #MachineLearning & #datascience - It lists down the most active data scientist on #github, free books, ipython notebooks, tutorials on github. buff.ly/2te2vDW
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Here is the perfect article for you to enhance your #MachineLearning skills! Pranav has listed down 7 ambitious ML GitHub projects from #NLP to #ComputerVision for you to try out. Includes plenty of tutorials and open source code links! #BigData #Python buff.ly/2YMn23K
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#AVBytes A brilliant use case of computer vision in #MachineLearning - a system that uses human pose estimation to identify violent individuals in a crowd! Check out the research paper, video and other details inside. buff.ly/2sOyPNa #ComputerVision
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๐ข Get access to the complete FREE Machine Learning Certification Course here: buff.ly/3gYaeze
#Python #machinelearning #Course #EDA #Certification #free
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For all the #DeepLearning beginners out there - here're 6 deep learning applications that you can build in minutes, using #Python. Let's begin. bit.ly/2zS9gAG
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Here're 28 cheat sheets for #MachineLearning, Data science, Probability, SQL & #BigData - pin them and use them for your ready reference! (Author: Swati Kashyap). bit.ly/2qP9ftK
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Graph theory is a fascinating concept, but how does it work? Explained here is the fundamentals and basic properties of graphs, along with different types of #graphs in this detailed article. There's even an implementation in #python to get you started! buff.ly/2O58HKm
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How many regression techniques are you aware of, apart from Logistics & Linear #regression? Get down to explore 7 most commonly used regression techniques with Sunil Ray and expand your understanding of these techniques, with this guide. buff.ly/2Mg8fp1 #BusinessAnalytics
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Here's a comprehensive guide to understand and learn hypothesis testing in #Statistics. Let's begin. buff.ly/2IeysSL #Analytics
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If you are looking at learning web scraping as a Beginner - this is where you should keep your eyes on! Using python's library - "BeautifulSoup" - it proves to be the easiest method - explained by Sunil Ray. bit.ly/2D0E8fW
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Let's learn about these 7 #TimeSeries forecasting techniques and compare them by implementing on a dataset, using #Python. buff.ly/2KH7f09 #datascience #machinelearning #statistics
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In order to become a complete Data Scientist, it is essential to know #mathematics behind #MachineLearning. This article covers various mathematical aspects you need to know to become a machine learning master, including #linearalgebra, probability & more- buff.ly/3xY0z2w
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Letโs determine the outcome of the harvest season, i.e. whether the crop๐พ would be healthy (alive), damaged by pesticides๐งด, or damaged by other reasonsโ๏ธ, with the help of Machine Learning - buff.ly/3iT6UHC
#MachineLearning #DataScience
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How to count number of people in crowd using #DeepLearning and #ComputerVision? Well, You get the hang of it by end of this tutorial. We will create an #algorithm for crowd counting with an amazing accuracy. Get set go! buff.ly/2SGclxw
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Get started with #PyTorch with four awesome case studies in #Python. In this article, Faizan also compares a neural network built from scratch in both numpy and PyTorch buff.ly/2UKfnhr
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For aspiring data scientist or an established one, start working on these projects to build up or polish your #datascience skills. buff.ly/2kF47Cy #MachineLearning
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Download this very useful #Infographic - it includes a step-by step process of cleaning text data in python using a #twitter case study. #Python buff.ly/2tvxBa4
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Multiple Linear Regression using Python and Scikit-learn: buff.ly/2VSjcGQ
#MachineLearning #DataScientists #Algorithms #LinearRegression #Python #Scikit-learn
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Did you know Time Series Modelling can make it easier when it comes to serially correlated data like website traffic? Here's a Tutorial to get started right from basics of #TimeSeries Modelling to its related techniques alongwith their R codes. buff.ly/2AP2RYu
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Python is one of the most powerful languages to perform machine learning tasks. Ram Dewani pens down 7 Python hacks, tips and tricks that will help you speed up your code for data science projects.
#python #datascience #dataanalytics buff.ly/2XBYzNk
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Cheat sheet with various codes and steps while performing exploratory #dataanalysis in #Python. buff.ly/2sFtZnp
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Can you classify tweets into positive & negative sentiments? Have you used Recurrent #neuralnetworks (RNNs) to deal with sequences in information. Dishashree Gupta explains the architecture of RNN right from scratch. buff.ly/2qpkpBU #MachineLearning #Python
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Which Python IDE do you prefer for your Data Science tasks?
PyCharm
Jupyter Notebook
VS Code
Other (Comment Below)
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Here're the most active data scientist alongwith best repositories, free books, notebooks on github to help you become better at #machinelearning & data science. bit.ly/2mXWFTG @Github
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These are 10 recommended #DataScience, #MachineLearning and #AI #Podcasts that every Data Scientist must listen to, to keep up with new advancements. buff.ly/2DPhve9
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Mark these 28 cheat sheets for Machine Learning, Data science, Probability, SQL & Big Data - for your ready reference. buff.ly/2o91YCi #BigData #MachineLearning
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Utilise your spare time this weekend, to learn building a FAQ #chatbot, with this comprehensive tutorial. Yogesh explains the complete process, taking example of building GST FAQ Chatbot. #NLP #Python buff.ly/2pyrnov
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Here are 5 data science projects to help you get the grip on the basics of tools & techniques and learn while you are working on it! buff.ly/2KusDkQ #BigData #BusinessAnalytics #BusinessIntelligence
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Pandas v1.0 is out! This major release contains lots of new and useful features. Here's Aishwarya Singh picking out the top 4 features and how you can use them in #Python. #DataScience
buff.ly/2RdtHzH
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A must-read tutorial by Pulkit Sharma to build your first crowd counting model using #DeepLearning and #ComputerVision! buff.ly/2SGclxw
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Let's get started with Altair - a very user-friendly visualization library in #Python which actually performs a lot of things with the minimal amount of code. buff.ly/2rnW6Wn #dataviz
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Did you know Python provides a lot of libraries for plotting and #datavisualization? Have a fun time learning this new visualization library in #python where you can do a lot of things with the minimal amount of code. #machinelearning #businessanalytics bit.ly/2IoYMce
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Want to build your own Siri or Google Assistant? Here's an awesome tutorial by Aravind to learn how to build your own speech-to-text model from scratch in #Python! #DeepLearning #NLP buff.ly/2lkzgOZ
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Hereโs a collection of 10 most commonly used #machinelearning algorithms with their codes in #Python and R. buff.ly/2dIgBGT
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Decision trees, random forest, #gradientboosting are popular algorithms used in all kinds of #datascience problems.A must read tutorial for every analyst(freshers also) to learn tree based modeling from scratch. bit.ly/1TPXKZn
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Decision trees, random forest, #gradientboosting are popular algorithms used in all kinds of #datascience problems. A must read tutorial for every analyst (freshers also) to learn tree based modeling from scratch. buff.ly/1TPXKZn
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Here's a tutorial to learn how to implement a #MachineLearning model using Flask framework in #Python. Let's begin. bit.ly/2sWa3Os
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A must-read tutorial by Pulkit Sharma to build your first crowd counting model using #DeepLearning and #ComputerVision! buff.ly/2SGclxw l
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We have explained the most commonly used 7 forms of regressions in a simple manner: #Linear Regression, Logistic #Regression, Polynomial Regression, Stepwise Regression, Ridge Regression, Lasso Regression, ElasticNet Regression.
Learn to implement these buff.ly/2RlimKG
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