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Hello All
These days Data Science is a big word in the market with almost all verticals focusing on this new domain and thus hiring a lot of Data Scientists.
The main issue which people who want to get into this exciting and promising field are facing is they don't know the following things:
1) What need to be studied
2) How much they need to study
3) RESUME/Profile building ( most important and most confusing)
4) Interview preparation.
I have been teaching my own "Get Data Science Job in 4 months" crash course since last 4 years now
I am able to help 200+ people to get job and enter this field of Data science.
Now I have decided to launch a series of videos on my RUclips channel where I will be providing all the highlights of my course so that I can help those who want to enter this field and can save their hard earned money as there are 1000s of courses available in the market right now and they charge lakhs of money from you and with false guarantees to train you to get into Data Science.
YOU WILL BE GUIDED TILL YOUR FIRST OFFER.
Here is the link to my first video of the series. I hope you guys will find it helpful and please do share your questions and feedback.
All the links and materials (including books) will be provided with proper project notes.
Links For Decision Tree, Random Forest, GBM and XgBoost
www.analyticsv...
www.analyticsv...
towardsdatasci...
towardsdatasci...
www.analyticsv...
towardsdatasci...
Link for SVM Support vector machine
www.analyticsv...
Link for Naive Bayes
www.analyticsv...
Books Link: For Linear regression and logistic Regression
drive.google.c...
For Statistics
drive.google.c...
Python Course: www.udemy.com/...
Here are some well-known companies that often hire data scientists:
Google
Facebook
Amazon
Microsoft
Apple
IBM
Oracle
Intel
Adobe
Cisco Systems
Uber
Airbnb
Netflix
Twitter
LinkedIn
Spotify
Tesla
Walmart
General Electric (GE)
Pfizer
Please note that this list is not exhaustive, and there are numerous other companies across various industries that hire data scientists. Additionally, the hiring practices and availability of data science positions can vary over time, so it's always a good idea to research and stay updated on current job opportunities.
1. Datasets for Regression and Classification
It contains many datasets that can be used for solving regression and classification problem statements. It is maintained by toronto university.
Link : goo.gl/irjNg4
2. Datasets for Text Mining
It contains data and R code for a book named "R and Data Mining".
Link : www.rdatamining...
3. Kaggle Competition
It is the best place to discover and analyze public available data. It is a repository of hundreds of public available datasets.
Link : goo.gl/fHKuII
4. UCI Machine Learning Repository
It is one of the biggest repository of public data sets that can be used for regression, classification and machine learning projects.
Link : goo.gl/ktMsFM
5. Amazon Public Datasets
It provides a centralized repository of public data sets at free of cost for the analytics community.
Link : goo.gl/jRMHro
6. Microsoft Research
It is a repository of many useful big datasets that can be used for practicing any data science and machine learning technique. For example, there is a dataset that identifies 38M tweets collected for the analysis of social media messages related to the 2012 U.S. Presidential election.
Link : goo.gl/YE4Vi4
7. Yahoo Datasets
Yahoo has released the largest ever machine learning dataset for researchers and engineers.
Link : goo.gl/ajcIpt
8. IMDB Database
It is a database of IMDB files which can be used for text mining and other data science projects.
Link : www.imdb.com/in...
9. AppliedPredictiveModeling (R package)
It is a R package containing datasets mentioned in book "Applied Predictive Modeling" written by developer of one of the most popular R package 'caret'.
Link : goo.gl/QPJAXB
#DataScienceCourse
#datasciencetrainings
#DataScienceforBeginners
#ravendersinghdahiya
#DataScienceCareer

[@ishdeepsingla6215]

very impressive video, keep posting the series...............👏👏👏👏

[@yogendra0026]

Very nice and informative videos....