### Important notes on Time Series Forecasting

Before talking about time series forecasting, let us understand time series data and some of their properties. We will explore why time series data are different from non-time series data. Time series data are the continuous or discrete sequences of observations that are recorded over certain (usually same) interval of time. For example, the daily

### Commonly used machine learning algorithms. Part II(Probability for machine learning)

Probability for Machine Learning Many events are filled with uncertainties and randomness. But some events are more likely than the others. In that case, we speak about the probability. “What is the likelihood of an event occurring?” For example, what is the likelihood that it is going to rain today? The answer to this question

### Commonly used machine learning algorithms. Part I (Linear algebra for machine learning)

It is always a hassle for students and machine learning engineers to choose the best machine learning algorithm for their data model. As I mentioned in earlier posts, I prefer to follow Occam’s razor which states that “simplest algorithm is the best algorithm” and No free lunch theorem, which states that “there is not a

### Data Science: Overview

One of the questions I always get from students and trainees who are beginner for data science is- “From where do I start my data science project ?” As we know, there is no data science without data and many think that gathering data is the very first step. But gathering data will be very

### Kaggle: The best place to learn data science and machine learning

Either you are a beginner or a proficient data scientist and/or machine learning engineer, there is always a lot to learn from Kaggle . Kaggle is a competition platform and provides us with variety of datasets. You can also read very interesting kernels written by many competitors. It is really helpful to understand different perspectives

### Data Preprocessing

Data preprocessing is one of the most time consuming but essential tasks for any data scientist. Preprocessing broadly means converting raw data into understandable format, which can then be processed using certain rules. One of the painful aspect of data is that most of them are unstructured and quite random sometimes. What are different types