Are you looking for a job, have submitted a few resumes, completed a few interviews and haven’t landed something yet? Don't worry, We are here to help you!
Are you facing challenges to transition from another domain to data science?? Or Struggling with how to crack interviews?? Or Not sure, how to prepare for data science?
Have you ever come across "Sampling" in statistics?
Have you thought, why do we need it?
We have prepared short notes for you to refer!!
Machine Learning Path
Path to be followed to become a Machine Learning Engineer
The most basic concept you need to know about Statistics to master Data Science is Probability!😉
It is one concept that is probably asked in every data science interview. That is why we have prepared last minute short notes on this topic.
Stand a chance to personally interact with an Industry specialist Mr. Sanket Patel a graduate from NIT, Surat. He is currently working as a Data Scientist at Amazon.
Do you get confused about what to do when you have more than 3 groups to test? Which test to use to find the difference among them? If yes, then don’t worry. We have prepared the last minute notes for you about ANOVA .
Did you know you can automate machine learning phases using Pycaret? Here's our post which has a simple tutorial on the same
Roadmap for learning NLP.
For more such update follow our LinkedIn.
Ever got confused what to do when you have less data? How to fit your model on less data and still make it perform better?
Then you should know about this technique!!
We have invited Mr.Paritosh Gupta a principal Data Scientist with 9+ years of experience in analytics, machine learning and data science.
NLP with Guided Project
Where you will learn: ✅ Understanding business problems ✅ Text data analysis ✅ Word embeddings ✅ Apply the deep learning algorithm ✅ Prediction of next word in the sentence ✅ How to get started in kaggle
Data Scaling Techniques
You also get confused in normalization, standardization?
Don't know where to use which one and why?
Meet our guest Vishal Pandey at a voice session at Telegram Messenger who is working as a senior ML researcher in Accenture and who has filed 4 patents in the field of data science within 3 years of his journey in data science.
Suppose you finished giving your exams and wanted to compare the topics that was asked in the exam and what were you expecting? Can you find some association between this?