Raksha Bandhan festival......at Government Degree College, Teliamura
The expression "Raksha Bandhan" (Sanskrit, literally "the bond of protection, obligation, or care") is now principally applied to this ritual. Until the mid-20th century, the expression was more commonly applied to a similar ritual, held on the same day, with precedence in ancient Hindu texts.
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@87antuds
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"Mahalaya: Invoking the Divine - A Soul-Stirring Journey into Devotion and Tradition"
Mahalaya Divine Celebration 🌟
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🎉 Celebrate the auspicious occasion of Mahalaya with us! 🙏
🕯️ Mahalaya marks the beginning of Navratri and Durga Puja, a time of divine significance and reverence for Goddess Durga. Join our special program as we pay homage to the goddess and invoke her divine blessings for a prosperous and joyous festive season ahead. 🌺
🎶 Immerse yourself in soul-stirring chants and devotional songs that will elevate your spirit and connect you with the divine. Witness mesmerizing performances by renowned artists, as we bring you a captivating visual experience of this grand celebration. 🎵
📅 Date: 14th October 2023
🔔 Don't forget to subscribe to our channel and hit the notification bell to stay updated on all our festive events and offerings. Let's come together and embrace the divine grace of Goddess Durga during this Mahalaya season! 🌟
🙏 May the blessings of the goddess fill your life with joy, prosperity, and love. Happy Mahalaya to one and all! 🙏
#Mahalaya
#Navratri
#DurgaPuja
#Festivals
#GoddessDurga
#Devotion
#Blessings
#Spirituality
#DivineCelebration
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PM acknowledges role of NEP in making India a knowledge hub
The Prime Minister, Shri Narendra Modi inaugurated Akhil Bhartiya Shiksha Samagam at Bharat Mandapam in Delhi today.
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Leaf 🍀 lifting in Slow Motion
Leaf lifting is a machine learning technique used for decision tree optimization, specifically in the context of boosting algorithms. It aims to reduce the complexity of decision trees by merging adjacent leaf nodes that yield similar predictions. The process involves iteratively combining leaf nodes in a bottom-up manner to create a more compact and efficient tree structure.
The leaf lifting procedure typically starts with an initial decision tree, which can be created using any base learning algorithm, such as CART (Classification and Regression Trees). Each leaf node in the tree represents a specific prediction or outcome.
The leaf lifting process begins by evaluating the similarity between adjacent leaf nodes. Various metrics can be used to measure the similarity, including the similarity of prediction values, impurity measures (such as Gini index or entropy), or statistical tests. If the similarity exceeds a certain threshold or satisfies a predefined condition, the adjacent leaf nodes are considered eligible for merging.
When merging two adjacent leaf nodes, the prediction value of the new merged node is often computed as the weighted average of the original leaf nodes' predictions. The weights can be determined based on various factors, such as the number of instances covered by each leaf node or the impurity of the data in each node.
After merging the leaf nodes, the decision tree structure is updated accordingly. The merged nodes are replaced with a single parent node, which becomes a new internal node in the tree. The parent node then becomes the entry point for subsequent branches, redirecting the decision-making process.
The leaf lifting procedure continues iteratively until no further merging is possible, or until a stopping criterion is met. This criterion can be defined based on factors such as a maximum tree depth, a minimum number of instances per leaf, or a predefined maximum number of leaf nodes.
Leaf lifting offers several benefits in decision tree optimization. By reducing the number of leaf nodes, it reduces the model's complexity and improves interpretability. It can also enhance the efficiency of the model by reducing memory requirements and speeding up prediction time. Moreover, leaf lifting can potentially mitigate overfitting by creating a more generalizable tree structure.
It is worth noting that different variations and extensions of leaf lifting exist, and the exact implementation details may vary depending on the specific boosting algorithm or decision tree framework being used.
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Gannam style in verson
Jarrod Walsh and Wolfgang have performed their version! Follow Jarrod on twitter @JarrodWalsh
LYRICS:
A girl who is warm and humanle during the day
A classy girl who know how to enjoy the freedom of a cup of
coffee
A girl whose heart gets hotter when night comes
A girl with that kind of twist
I'm a guy
A guy who is as warm as you during the day
A
guy
who one-shots his coffee before it even cools down
A guy whose heart bursts when night comes
That kind of guy
Beautiful, loveable
Yes you, hey, yes you, hey
Beautiful, loveable
Yes you, hey, yes you, hey
Now let's go until the end.
Oppa is Gangnam style, Gangnam style
Oppa is Gangnam style, Gangnam style
Oppa is Gangnam style
Eh- Sexy Lady, Oppa is Gangnam style
Eh- Sexy Lady oh oh oh oh
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