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Deep learning is a subset of machine learning that uses neural networks to learn from data.
Deep learning involves training neural networks with large amounts of data to make predictions or decisions.
It is used in image recognition, natural language processing, and speech recognition.
Deep learning models can automatically learn to extract features from raw data.
It requires a lot of computational power and data to train ...
Reinforcement Learning is an advanced branch of AI that involves training agents to make decisions based on rewards and punishments.
Reinforcement Learning involves an agent interacting with an environment and learning from the rewards and punishments it receives.
It has been used in various applications such as game playing, robotics, and recommendation systems.
Some popular algorithms in Reinforcement Learning include Q...
I applied via Job Portal and was interviewed before May 2023. There were 3 interview rounds.
LSTM is a type of RNN with additional memory cells to better capture long-term dependencies.
RNN stands for Recurrent Neural Network, while LSTM stands for Long Short-Term Memory.
LSTM has additional memory cells (input, forget, output gates) to better capture long-term dependencies.
RNN suffers from vanishing/exploding gradient problem, while LSTM helps alleviate this issue.
LSTM is better suited for tasks requiring long-...
Top trending discussions
I applied via Company Website and was interviewed in Mar 2024. There were 2 interview rounds.
Pyspark, Python and Machine learning questions
I applied via Referral and was interviewed in Nov 2024. There was 1 interview round.
Cancellation in the number of bookings in an app has increased exponentially in the past few weeks, How would you conduct an RCA on the same.
I applied via Referral and was interviewed in Sep 2024. There were 5 interview rounds.
1 python and 1 SQL coding along with ML questions mostly related to monitoring and basic ML
1 python code and also related to ML ...the recruiter came with a dataset to solve
Guestimates, project discussions and Case Studies
Project indepth discussion and case study related Fraud Detection
I applied via Company Website and was interviewed in Mar 2024. There were 2 interview rounds.
Pyspark, Python and Machine learning questions
I applied via Referral and was interviewed in May 2024. There was 1 interview round.
I solved a problem by using machine learning algorithms to predict customer churn for a telecom company.
Identified relevant data sources such as customer demographics, usage patterns, and customer service interactions.
Preprocessed and cleaned the data to handle missing values and outliers.
Built and trained a machine learning model using algorithms like logistic regression and random forest.
Evaluated the model's perform...
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