JNTUK R20 3-2 Compiler Design Material/Notes PDF Download

JNTU KAKINADA B.Tech 3-2 R20 Compiler design material download. Compiler design lecturer notes

UNIT I: Lexical Analysis: Language Processors, Structure of a Compiler, Lexical Analysis, The Role of
the Lexical Analyzer, Bootstrapping, Input Buffering, Specification of Tokens, Recognition of Tokens,
Lexical Analyzer Generator-LEX, Finite Automata, Regular Expressions and Finite Automata, Design of
a Lexical Analyzer Generator.

UNIT II: Syntax Analysis: The Role of the Parser, Context-Free Grammars, Derivations, Parse Trees,
Ambiguity, Left Recursion, Left Factoring, Top Down Parsing: Pre Processing Steps of Top Down
Parsing, Backtracking, Recursive Descent Parsing, LL (1) Grammars, Non-recursive Predictive Parsing,
Error Recovery in Predictive Parsing.

UNIT III: Bottom Up Parsing: Introduction, Difference between LR and LL Parsers, Types of LR
Parsers, Shift Reduce Parsing, SLR Parsers, Construction of SLR Parsing Tables, More Powerful LR
Parses, Construction of CLR (1) and LALR Parsing Tables, Dangling Else Ambiguity, Error Recovery in
LR Parsing, Handling Ambiguity Grammar with LR Parsers.
 

UNIT III: Syntax Directed Translation: Syntax-Directed Definitions, Evaluation Orders for
SDD’s, Applications of Syntax Directed Translation, Syntax-Directed Translation Schemes,
Implementing L-Attributed SDD’s. Intermediate Code Generation: Variants of Syntax Trees, Three
Address Code, Types and Declarations, Translation of Expressions, Type Checking, Control Flow,
Backpatching, Intermediate Code for Procedures

UNIT IV: Run Time Environments: Storage Organization, Run Time Storage Allocation, Activation
Records, Procedure Calls, Displays, Code Optimization: The Principle Sources of Optimization, Basic
Blocks, Optimization of Basic Blocks, Structure Preserving Transformations, Flow Graphs, Loop
Optimization, Data-Flow Analysis, Peephole Optimization


UNIT V: Code Generation: Issues in the Design of a Code Generator, Object Code Forms, Code
Generation Algorithm, Register Allocation and Assignment

 

JNTUK R20 3-1 Compiler Design Material/Notes PDF Download Set-I

JNTUK R20 3-1 Compiler Design Material/Notes PDF Download Set-II

JNTUK R20 3-1 Compiler Design Material/Notes PDF Download Set-III

JNTUK R20 3-1 Compiler Design Material/Notes PDF Download Set-IV

JNTUK B.Tech 3-2 R20 Machine Learning Material

 JNTUK B.Tech 3-2 R20 Machine Learning Material for all 5 units are now available. The materials provided here is prepared in an easy for read and understating.

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Unit I:

Introduction- Artificial Intelligence, Machine Learning, Deep learning, Types of Machine Learning
Systems, Main Challenges of Machine Learning.

UNIT-I Chapter-I Download Here

Statistical Learning: Introduction, Supervised and Unsupervised Learning, Training and Test Loss,
Tradeoffs in Statistical Learning, Estimating Risk Statistics, Sampling distribution of an estimator,
Empirical Risk Minimization

UNIT-I Complete Download Here

Unit II

Supervised Learning(Regression/Classification):Basic Methods: Distance based Methods, Nearest
Neighbours, Decision Trees, Naive Bayes

Linear Models: Linear Regression, Logistic Regression, Generalized Linear Models, Support Vector Machines
Binary Classification: Multi class/Structured outputs, MNIST, Ranking.

UNIT-II Download Here

Unit III

Ensemble Learning and Random Forests: Introduction, Voting Classifiers, Bagging and Pasting,
Random Forests, Boosting, Stacking.

Support Vector Machine: Linear SVM Classification, Nonlinear SVM Classification SVM Regression,
Naïve Bayes Classifiers.

 UNIT-III Download Here

Unit IV

Unsupervised Learning Techniques: Clustering, K-Means, Limits of K-Means, Using Clustering for
Image Segmentation, Using Clustering for Preprocessing, Using Clustering for Semi-Supervised
Learning, DBSCAN, Gaussian Mixtures.

Dimensionality Reduction: The Curse of Dimensionality, Main Approaches for Dimensionality
Reduction, PCA, Using Scikit-Learn, Randomized PCA, Kernel PCA

  UNIT-IV Download Here

Unit V

Neural Networks and Deep Learning: Introduction to Artificial Neural Networks with Keras,
Implementing MLPs with Keras, Installing TensorFlow 2, Loading and Preprocessing Data with
TensorFlow.

UNIT-V Download Here

JNTUK B.Pharmacy 3-1 (R20) Sem PCI Syllabus Materials Download

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 JNTUK B.Pharmacy 3-1 (R20) Sem Materials Download  

MEDICINAL CHEMISTRY-II (BP501T) Download Here

INDUSTRIAL PHARMACY – I (BP502T) Download Here

PHARMACOLOGY-II (BP503T) Download Here

PHARMACOGNOSY  AND PHYTOCHEMISTRY-II (BP504T)  Download Here

PHARMACEUTICAL JURISPRUDENCE  (BP505T) Download Here