Maths, Statistics, ML & DL List of Books: https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md
DS Books Links: http://datasciencemasters.org/
Statistics Learning: https://www.statlearning.com/
15 Completely Free Machine Learning and Deep Learning Books: https://python.plainenglish.io/15-free-data-science-deep-learning-books-4af882135fad
Free Books Download: https://leanpub.com/
Mathematics for Machine Learning: https://drive.google.com/file/d/1XOv9XR1jhGhmgk6kuJOmSJ0wPae_9cqC/view
Q. Can you mention the different skills we need to have by the end of the course.like for an example of developing algorithms in such a way? Can you please mention the skills which we need?
Srikant Answer:
1. Understanding a business problem and mapping it to the data science domain.
2. Obtain and clean Data for data analysis.
3. Perform analysis to gain insights from data using statistical and visualisation methods/tools.
4. Build a variety of classical ML and state of the set deep learning models from scratch.
5. Modify existing ML and DL algorithms to meet real world needs.
6. Read cutting edge research papers in ML and DL.
7. Debug and understand ML and Dl models.
8. Deploy ML/DL models into production.
Q. One query regarding DSML course, In DSML we don’t develop any kind of software development or we do any other development regardless of software development.
As a DSML engineer we don’t need to develop software for data analytics or ML engineer.what we develop so that we can become a DS or ML or DA Engineer confidently.
Srikant Answer: You would write code and build software, but not of the same nature as a typical software engineer. A good software engineer uses Data Structures, algorithms, databases, distributed systems, OOPs etc to write scalable and reliable software. A Data scientist often writes code/software to analyse data and build and deploy ML models, which needs different skills.
Q. As in the majority of interviews companies are asking for relevant experience in DA/DS. Candidates like me who are transitioning their career to DS, I don’t think we will be eligible to sit in the interview for those companies due to no relevant experience . So how scaler will help us in those scenarios? And making us sit for those interviews?
Srikant Answer:Our careers team talks to many such companies and convinces them to use the MBE-test and mock interview feedback to showcase your expertise to be on par with folks with experience. Many of the case studies we learn in the program are another key to cracking interviews as you get first hand experience of solving problems as if you were working as a data scientist/analyst.
Kaggle – Data Science Community
Kaggle is basically a platform for data science…
There are 4 major components
- COMPETITIONS:
They host machine learning competitions… Where data scientist from across the globe compete… and anyone can compete - NOTEBOOKS:
people can write python notebooks on data explorations, visualization machine learning deep learning and lot more… - DISCUSSIONS:
discussion forums where people post questions and general discussions about data science… Latest trending etc - DATASETS:
datasets is where people submit opensource data… Anyone can download the data and use it for explorations .. either visualisations or training machine learning models etc
1st Mentor Session
Mentor Session
New DS – 10-12
Advisory DS – 18-22
Senior DS – 35-42 – Mentor
Principal DS – 65-70
2007 – Finance Analyst
2015 – Senior Data Science
Live Classes
Teaching Assistant
Mentor Session – (Experienced DS)
12 Mock Interviews – Good Interview Preparation
12 session in 1 week in Jan
Mentor’s Area of Expertise:
Data engineer – SQL, process, extract data
Python
Machine Learning algorithm
NLP Algorithm – Theory
Mentor chat how long
**************************
Get into DS role as soon as possible when you are doing the course.
DA – 2 years, we cant get
Good LinkedIn Profile about what you do and your value to the company
Document your project code and publish on GitHub.
Live Project with Scaler
Anybody can write anything in resume, but if they see the code on things that they are looking for, then hiring chances will increase.
Coding Platform –
CodeForces
CodeChef
Kaggle – Kaggle ranked based on contribution, notebook uploading, challenges solved
HackerRank
Jupyter Notebook – for testing codes before implementation
Resume – Rework on resume
CV Review
I didn’t have enough guidance back then, eventually I realized I need stablity and understood data science is where my real interest lies.
I did my DS course along with job. This are the projects I have done.
Depth of knowledge
Practice more often as much as possible.
LOW Vacancy for DS thaan DA –
Market Down – Recession
1 Year Testing Time
Attend Class Regularly
*************
Mentor Session
Only one DS (manager) required to build model, but many visualization
Planning to continue in IBM and not switching
Recession or Ukraine War can’t be control
Are you able to provide the kind of support expected from you?
Q. Age – 31 Year for career change
Irrelevant experience before doing DS
What is my priority?
Latest Research – iamge processing, NPL
How to lookup, reaad, analyze Research Paper.
Where can we see that ?
How was my session? How am I different than other mentee?
open to learning, motivation,
Focus on Process