Machine Learning

  1. Text Classification using LSTM in Keras (Review Classification using LSTM)
  2. What is Regularization in Machine Learning (Ridge Regression and Lasso Regression)?
  3. Linear Regression Part-1 ( What Assumptions to Check While using Linear Regression)
  4. Introduction to Machine Learning (Supervised Learning, Unsupervised Learning, Reinforcement Learning)
  5. Scratch Implementation of Stochastic Gradient Descent using Python.
  6. Amazon Review Text Classification using Logistic Regression (Python, Sklearn, Bag of Words)
  7. Interpretation of Machine Learning Models
  8. Back-Propagation in Deep Learning
  9. Adagrad Optimization Algorithm
  10. Multilayer Neural Network vs Classical Neural Network
  11. Deep Learning Interview Question
  12. Widely used Distances in Machine Learning
  13. Various Evaluation metrics for Machine Learning Classification Tasks (Confusion metric, precision, recall, accuracy score, f1-score, etc)
  14. All You Need to Know about Activation Functions (Sigmoid, Tanh Relu, Leaky Relu, Relu-6, Softmax)
  15. Basics of Random Forest that You Need to Know.
  16. FLASK API to calculate WER, MER for text comparison in Python.
  17. A basic introduction to Random Forest.
  18. How will you choose a machine learning model for your problem?


  1. How distributions are used to solve real life problems?
  2. All You Need to Know About Sampling Distribution in Statistics
  3. A Detailed Understanding of Various Distributions in Statistics (Explained Simply)
  4. Co-Variance and it’s interpretation in statistics.

General Tips

  1. RoadMap to excel in Computer Science and get a package of 20+ LPA.
  2. How to prepare data structure and algorithms for machine learning and data science interviews?
  3. How to use Linkedin to get Machine Learning or Data Science interview Calls?
  4. Which Laptop to Buy for Machine Learning and Deep Learning?
  5. Everything You Need to Know about Machine Learning Syllabus to Become a Data Scientist?
  6. Get Feedback on You Resume for Software Engineering/ Machine Learning/ Data Science Jobs
  7. Top Skills You Must Not Avoid to Become a Great Data Scientist
  8. Being a data scientist, how to Establish Your Self as a Brand?
  9. How to learn python without joining any online or offline course in 4-5 days/

Gate CSE

  1. All about IIT Gandhinagar (Admission, Interview, Placements, Research, Faculty) M.Tech Computer Science
  2. Which College to Choose to pursue M.Tech for Good Placements, if not Getting Old IITs?
  3. Which one to choose between New IITs and Established NITs, a detailed comparison (Placements, Infrastructure, Research, etc)
  4. Why You Should Appear for GATE Computer Science & Engineering?
  5. The GOD Strategy to Get Good Marks in GATE CSE, Computer Organization & Architecture Section.

Our Free Services

  1. Data Structure and Algorithm to Crack Product Based Companies.
  2. Get Feedback on Your Resume for Software Engineering/ Machine Learning/ Data Science Jobs.
  3. Mock Interview for Machine Learning or Data Science Profile (Feedback on Data Science or Machine Learning Job Preparation)