machine learning

In this post we will understand basic concepts of word2vec and see how to implement and use it.

When we are working with ML, we are most of the time working with vectors in higher dimensions. This makes it very difficult to actually visualize and view data. Above are few of the methods which we can use to visualize data.

In this blog post let’s see in details what is TD-IDF

In this blog post we will understand bag of words model and see its implementation in detail as well

Word embedding is a very important concept in NLP. Its very important to understand what is it and what it is used for.

NLP

NLP is a branch of machine learning which mainly deals with text language and making it able for a system to understand human language.

We look into libraries like spacy, nltk and scikit-learn and implement some basic things used with NLP.

Till now we have seen basics on NN’s and at this stage we can create our first Neural Network

Let’s look at loss function with Keras in detail and implement it in our neural network

We have seen earlier the entire purpose of to optimize weights so as to reduce loss. Let’s see in detail different optimization functions we can use with neural networks

Softmax is a special kind of activation function which use mostly used as the last layer. The final output of an NN needs to be human understandable so in the output we would need to be able to get probabilities in case of multi classifier problem.

In this post we look deep into activation function.

In these series of blog posts we will look in detailed implementation of neural networks using Keras and also more deeply understand how neural networks work.

In this post we will see about logistic regression, this post is in continuation of liner regression which we saw before. Make sure to read the previous post in detail before reading this.

In this post we will see what exactly is linear regression and it will help us better understand NN’s.

This post can be skipped, but i think it provides a good foundation for understanding NN’s

This series of blogs and following blogs will be part of machine learning basics where will understand and implement machine learning algorithms.