My personal space where I scribble whatever funny thoughts come to my mind. Actually, that is not entirely true. A lot of random thoughts enter and leave my mind all the time and the blog contains only a largely drilled down and censored subset of them.
Also, there are reviews of certain movies that have fascinated the viewer in me.
I would say the time you spent here would not be regretted.
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TV Review : Sherlock - The Abominable Bride
Title : Sherlock - The Abominable Bride Language : English Year : 2016 Director : Douglas Mackinnon Genre : Crime, Drama, Mystery IMDB Link Watch trailer on Youtube Lead Role : Benedict Cumberbatch, Martin Freeman, Una Stubbs
After almost two years of baited anticipation, the hat detective and his doctor friend is back, this time in what apparently is a time twisting episode, as the plot unravels itself in the nineteenth century. Sherlock fans, do not be disheartened. The times may have changed, horse carts may have replaced motor cars and certain socio-political situations might be from the past, but the super confident-arrogant nature of Mr. Holmes and the helpful, concerned and rebuking nature of the good old Watson remain intact in this "special" episode. Though this is an off-episode, I would advise you to watch the first three seasons before you watch this (if you have not watched already).
So, what is the abominable bride all about? To be short and not to let the spoilers away, this is the tale of Emilia Ricoletti, who has risen from her grave after committing suicide in public. And she does not sit quiet after her comeback. Instead, what ensues is a murder spree. Obviously, Sherlock gets involved. There are certain paranormal elements in the way the story is presented, and some scenes may give you a horrifying chill.
Is the abominable bride all about one dead woman walking? No. I am not gonna spoil anything for anyone, but you would be in for some surprises down the line. The first one being Mycroft Holmes himself. Nothing more about the story. Better watch and enjoy.
What I love about Sherlock is the superlative direction and the fascinating dialogues. And, there is no death of neither in this. Performances, as usual, are top class. While the abominable bride gives you some answers, it opens a set of questions.
You might be familiar with the term Machine Learning. Worry not if you have not, cause I have tried to give a gist of the concept here. The term has been in the limelight of late and has been tossed around rather liberally to denote anything related to artificial intelligence, robotics, and data mining. Machine Learning, as the name suggests, could simply mean the field of study of enabling the “machines” (computers) to “learn” from past experiences and make informed decisions in the future. Wait a minute! Learning from past experiences is something humans do, right? Exactly! The computer folks want computers to behave more and more like us. As if there aren't enough of us already. As the machines are becoming more like us, we are becoming more like them. Introspection time! Most of us wake up every morning like clockwork! Then we rush through the morning routines - get dressed, wade through the traffic, and reach our offices or schools or wherever people expect us to be. We spe
Before The Judgement I believe I must begin by addressing the pressing question - Was planning a vacation in the midst of a pandemic a recommended move? No. Yet we went ahead with it. Here is why. We (Nithya & I) were newly married, and our vividly planned vacation at the island of Langkawi was stolen away from us by the virus. Our stay in Delhi was coming to an end due to job-related moves, and we felt it would be a waste not to utilize this opportunity in exploring at least one of the tourist hot spots easily accessible from the national capital region. Let us end this section by answering another question - Are the reasons listed above good enough to risk a vacation during a pandemic? No. We had taken a calculated risk. Arrival at Manali There are two phases to this - planning and execution. We had not started planning with Manali in mind. There were numerous choices - starting from Jaipur and Amritsar to Nainital, Shimla, and Manali. After a bit of reading and deliberations,
You can’t conclude a discussion on Machine Learning without mentioning classification. Classification is a machine learning technique where the machine is trained to predict the label of the given input data. Alright, let’s cut the jargon and get some real-world examples. Oranges and Bananas. Let’s assume that we have a box of fruits that contain some oranges and some bananas. You are asked to pick one fruit at random and tell if it is an orange or a banana. Pretty basic, right? For us, it is straightforward. We would know the answer at first sight. But, how would a computer be able to tell the difference? In classification, the machine would first be trained on some pre-labeled data. It would be shown an orange and we would tell it that the fruit is an orange. The machine would study the orange and remember its features - orange color and round shape. Then it would be shown a banana and the process is repeated. What are these features? A feature is anything that helps us uniquely labe