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Algorithms, Part I
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This course covers the fundamentals of data transformation and ingestion using libraries & pipelines.
Learn to execute a machine learning project from start to finish, including problem statement, EDA, feature engineering, and model training, in under an hour with Krish Naik.
Learn to implement end-to-end Data Science projects using Docker with Krish Naik's tutorial. Expect 1-2 hours of material covering Docker installation, image creation, and more.
Krish Naik's 2-3 hour program offers in-depth understanding of Heap Sort, Binary Tree, Min Heap, Max Heap Tree, and prepares you for FAANG interviews with relevant questions.
Explore sorting algorithms like selection, bubble, and insertion sort in a 1-2 hour material by Krish Naik. Ideal for understanding array sorting and algorithm implementation.
Learn end-to-end ML project implementation with Dockers and Github Actions from Krish Naik. Master dataset preparation, model training, performance metrics, and app deployment in 2-3 hours.
Learn all about search algorithms with interview-based questions in a 2-3 hour program by Krish Naik, featuring Priya Bhatia. Topics include Linear Search, Binary Search, and Ternery Search.
Learn statistics for data science in 6 hours with Krish Naik. Master descriptive and inferential stats, hypothesis testing, and data analysis techniques.
Dive into machine learning with Krish Naik's 7-hour program, covering topics from AI, ML, DL, Data Science to practical implementation of various algorithms.
Dive into deep learning with Krish Naik in a 6-hour program, covering topics from AI, ML, DL, Data Science to practical implementation of ANN and CNN.
Krish Naik's online session offers an introduction to statistics in data science, covering topics like sampling techniques and frequency distribution. Expect a 1-2 hour workload.
Krish Naik's online material offers a deep dive into Web 3.0, covering topics like mining processes, smart contracts, tokenomics, and the metaverse in 1-2 hours.
Learn to implement a face-matching application using deep learning with Krish Naik. This 3-4 hour program covers data collection, project architecture, and web app implementation.
Learn to implement Perceptron in Deep Learning using Python from scratch with Krish Naik in a 1-2 hour program.
Krish Naik's 1-2 hour video tutorial offers a comprehensive review of all major deep learning optimizers, including Gradient Descent, SGD, SGD with Momentum, Adagrad, Adadelta, RMSprop, and Adam Optimizer.
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