Today is the last day of my B’day month (31st July) and its been approx 10 days, I’m evolved in scraping projects for my White Label Marketing company.
Things I’ve learned till now in this company is only scraping – how to scrape websites in more efficient way, whether its Java Script’s website or HTML based.
In the very starting of these projects I was bit nervous or do not wanted to do this job, But as time goes by it seems little interesting now, and now the time came that I can post some articles on this topic too, as famous saying is “You must learn, Where or whatever you can from”

The Perceptron Algorithm is one of the oldest Machine Learning algorithm developed in 1950’s.

The motivation behind this algorithm comes from the study of a biological neuron in order to replicate the intelligence brain to develop Artificial Intelligence.

This is how a neuron works –

A neuron takes input signals from its surroundings using Dendrites

and send to the cell body. Once the received signal crosses the threshold point, the neuron gets fired/activated and passes the signal via Axon to the Synaptic terminals..

A basic Perceptron works on the same principle. It is used in binary classification problems,

Fig. 1 Neuron

Just as we can see the figure of a perceptron, we pass the inputs via the some weights. And then we sum the product of the weights and the inputs. Weights are something that we learn overtime from the data that is given to us. That part is the “Learning” in Machine Learning, This whole summation is passed to an activation function which generates probability of a class in binary classification.

How we learn weights –

A Perceptron seeks to minimize the loss function which is defined as –

L = – Σ (yi * (xi^T * w))

which is summation of y and the product of x and w over all the data points where y is not same as that of sign of x*w.

By minimizing L, we try to predict the correct label.

After calculating the loss function using the above formula, we update the weights using the below equation.

W(new) = W(old) – ( η * ΔL )

Here, ΔL cannot be solved analytically, but it gives us a sense of direction in which L is increasing in w. η is a constant and also called learning rate. It sets the speed with which we learn.

The Loss calculated using the W(new) is less than the loss calculated using W(old). This procedure is one step of optimizing the objective function. After repeating it for certain number of times, we get the value of W that fits well to the data and produces a low loss. This is procedure of updating the value of weights using the delta of the loss function is called Gradient Descent.

And after multiple iterations of Gradient Descent, we have the optimized value of W which is then used to predict the class of the incoming data.

One thing to notice about Perceptron is that if the data is not linearly separable, then its not possible to converge the value of W using Gradient Descent, which leads to the bad fit and wrong predictions.

You want to become successful. You can feel that there is more to life than what you are presently enduring. It has crossed your mind more than once that maybe you are doing things the wrong way. You need a new approach to ensure you give life your best shot at becoming one of the individuals that history can never forget. You can make your indelible mark on the line of history as a successful person by trying some Success Rituals.

You are right about needing an approach to attain success. Success Rituals shares insight into steps that successful individuals conduct daily and some that you might want to implement in your life.

The natural order of life is that things go through stages. Take for instance the process that it takes to create a child. In the womb, there are a series of steps, and after birth, there is another. Nevertheless, each child develops at a different pace. Some kids walk or talk before what is considered the “expected time” for them to do so.

Success Rituals are processes that individuals endure to become prosperous. Achievements during the stages are different for everyone. However, there are similarities in each stage of the Success Rituals, just as how there are similarities in the stages to produce a child, but the outcome differs. Success Rituals have certain fundamentals that every successful individual had to do, and some which they had to learn how to overcome. Likewise, you must decide without any form of doubt that you too will have to work hard and overcome whatever obstacles you will encounter on your journey.

You might be the one that will develop before the expected time frame for one to become a success. Do not delay for another minute. It is time to discover empowering Success Rituals, which will assist you to conquer your fears and progress on your destined journey of prosperity.

Its very easy to get overwhelmed by the volume of materials/resources available on internet these days to study Neural networks and Machine learning.

When I started, I could not decide what to learn from where. There were multiple excellent courses/blogs/tutorials which I felt to be ‘must do’. This information overload made me end up doing nothing at worst or wasting a lot of time to decide which one to pick at best.

A few times I stumbled upon some suggestions of how to structure my learning and handle this information overload. This blog contains list to such resources which proved invaluable to me to structure my learning and move fast.

1. This describes how to structure your project into tasks and sub tasks and allocate appropriate time resources to them:

Majority of us don’t get the opportunity to attend courses in an Ivy league university in-person. I have learned a lot from the lectures of courses hosted on MIT OCW and Stanford online. Andrej Karpathy’s advice on how to do well in your courses teaches a lot things about human memory and work ethics you should follow while doing these courses. Most importantly, experiment what works best for you instead of just following all of the points.

Tips from writing a good paper to finding a compatible advisor to structuring your approach for navigating through research ideas and other important guidelines, this article from Andrej Karpathy covers a lot things you will need to survive in a research community. You need not be thinking to go for a PhD in order to use this valuable discussion.