Daily DeepLearning

Daily-Dearn

Basic Computer Course

Data structure

• 01 Basic concepts and algorithm evaluation
• 02 Linear Table
• 03 Stack and Queue
• 04 Tree and Binary Tree
• 05 pictures
• 06 Search
• 07 sort

operating system

• 01 Basic concepts of operating system
• 02 Development and classification of operating systems
• 03 Operating environment of the operating system
• 04 Processes and threads
• 05 Processor Scheduling
• 06 Process synchronization
• 07 Deadlock
• 08 Content Management Concept
• 09 Virtual memory management
• 10 File System Basics

Computer network

• 01 Computer Network Overview
• 02 Computer network structure system
• 03 Communication Basics
• 04Nei's Code and Shannon's Theorem
• 05 Transmission medium
• 06 Physical layer equipment
• 07 Functions of the data link layer

?Python

Quick Start

• Day01: Variables/Strings/Numbers and Operators
• Day02: List/tuple
• Day03: Dictionary/set
• Day04: if/loop
• Day05: Calling function/defining function/function parameters
• Day06: Iteration/list generator/generator/iter
• Day07: Advanced function/return function/anonymous function/decorator
• Day08: Classes and instances/restricted access/inheritance and polymorphism
• Day09: __slots/@property/multi-inheritance/custom class/enumeration class
• Day10: Error handling/debug/document testing/unit testing
• Day11: File Reading and Write/StringIO/Operate Files
• Day12: Multi-process/Multi-thread/ThreadLocal
• Day13: datetime/collections/struct
• Day14: Coroutines/async/async/await/aiohttp
• Day15

Use of data science packages

numpy

• Create ndarray
• Data types and operations
• Indexing and slicing
• Matrix Operation

pandas

• Loading data
• Row selection
• index
• Filter
• Update the ranks
• Add rows and columns
• Data sorting
• Data aggregation
• Clean the data
• Time data

matplotlib

• Linear diagram
• bar picture
• Pie bar chart
• stack picture
• Linear filling
• Hist picture
• Point diagram
• Timing diagram
• Sub-picture

?️Machine Learning Theory

• Logical regression
• EM Algorithm
• Integrated learning
• Random Forest and GBDT
• ID3/C4.5
• K-means
• KNearest Neighbor
• Bayes
• xgboost/lightGBM
• Gradient Boosting
• Boosting Tree
• Return to the tree
• XgBoost
• GBDT classification
• GBDT Return
• LightGBM
• CatBoost

?‍♀️Deep Learning Theory

• Word2Vec
• BatchNorm
• Dropout
• CNN
• RNN
• LSTM
• Attention
• ELMo
• Transformer
• BERT
• ALBERT
• XLNet

?️NLP related

• theory
  • Word2Vec
  • LSTM
  • ELMo
  • ALBERT
  • XLNet

?️Practical Machine Learning Battle

• numpy

  • Create ndarray
  • Data types and operations
  • Indexing and slicing
  • Matrix Operation

• pandas

  • Loading data
  • Row selection
  • index
  • Filter
  • Update the ranks
  • Add rows and columns
  • Data sorting
  • Data aggregation
  • Clean the data
  • Time data

• matplotlib

  • Linear diagram
  • bar picture
  • Pie bar chart
  • stack picture
  • Linear filling
  • Hist picture
  • Point diagram
  • Timing diagram
  • Sub-picture

?‍♀️ Deep Learning Practical Battle

• tensorflow

  • Helloword
  • Basic
  • linear_regression
  • logistic_regression
  • world2vec
  • Basic image classification
  • TFHub text classification

• pytorch

  • start
  • autograd
  • NeuralNetworks

Big data related

• Hadoop

  • introduce
  • Cluster construction 01
  • Cluster construction 02
  • Cluster construction 03
  • HDFS01
  • HDFS02

• Hive

?Step on offer

• Day01: Search in a 2D array
• Day02: String substitution
• Day03
• Day04
• Day05
• Day06
• Day07
• Day08
• Day09
• Day10
• Day11
• Day12
• Day13
• Day14
• Day15

Work contact: [email protected]