MACHINE LEARNING TRAINING IN NOIDA
BEST MACHINE LEARNING TRAINING IN NOIDA / MACHINE LEARNING TRAINING INSTITUTE IN NOIDA
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Are you Looking for the Best Institute for Machine Learning Training in Noida? DUCAT offers Machine Learning training courses with live projects by expert trainers in Noida. Our Machine Learning training program is specially designed for Under-Graduates (UG), Graduates, working professionals, and also for Freelancers. We provide end to end learning on Machine Learning Domain with deeper dives for creating a winning career for every profile.
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Why To Choose an Artificial Intelligence Course In Noida?
Learning artificial intelligence training in Noida has given us the best career option because we are living in the world of Alexa, Google, or Siri which manages the calendar and works according to us. Artificial intelligence has entered each fields like shopping purchases, music, and other platforms. It is one of the known professions these days where many of students want to get admission and have a bright future. It has exponential growth with rising technology in the world. It helps in better decision making as they give final output through the machine. It gives better decision-making to the recruiters.
PYTHON + DATA SCIENCE + MACHINE LEARNING
Python is mainly stated as high-level, general-purpose programming language, which emphasizes code readability. Syntax helps programmers to express their concepts in a few general "lines of code" when compared with other promising languages, like Java or C++. Through our courses, you can easily construct clear programs, on both large and small scales. As the importance of Python programming language is gaining huge popularity, therefore; the need to understand and know the language is increasing among people. When you think about Python training, you must look for a Ducat expert help.
MODULE 1: PYTHON ESSENTIALS
- What is Python..?
- A Brief History of Python
- Why Should I learn Python..?
- Installing Python
- How to execute a Python program
- Write your ļ¬rst program
- VARIABLES & DATA TYPES
- Variables
- Numbers
- String
- Lists , Tuples & Dictionary
CONDITIONAL STATEMENTS & LOOPS
- if...statement
- if...else statement
- elif...statement
- The while...Loop
- The for....Loop
CONTROL STATEMENTS
- continue statement
- break statement
- pass statement
FUNCTIONS
- Deļ¬ne function
- Calling a function
- Function arguments
- Built-in functions
MODULES & PACKAGES
- Modules
- How to import a module...?
- Packages
- How to create packages
CLASSES & OBJECTS
- Introduction about classes & objects
- Creating a class & object
- Inheritance
- Methods Overriding
- Data hiding
FILES & EXCEPTION HANDLING
- Writing data to a ļ¬le
- Reading data from a ļ¬le
- Read and Write data from CSV ļ¬le
- try...except
- try...except...else
- ļ¬nally
- os module
DATA SCIENCE
MODULE 1: GETTING STARTED WITH PYTHON LIBRARIES
- what is data analysis?
- why python for data analysis?
- Essential Python Libraries
- Installation and setup
- Ipython
- Jupyter Notebook
MODULE 2: NUMPY ARRAYS
- Creating multidimensional array
- NumPy-Data types
- Array attributes
- Indexing and Slicing
- Creating array views and copies
- Manipulating array shapes
- I/O with NumPy
MODULE 3: WORKING WITH PANDAS
- Installing pandas
- Pandas dataframes
- Pandas Series
- Data aggregation with Pandas DataFrames
- Concatenating and appending DataFrames
- Joining DataFrames
- Handling missing data
MODULE 4: DATA LOADING, STORAGE AND FILE FORMAT
- Writing CSV ļ¬les with NumPy and pandas
- HDF5 format
- Reading and Writing to Excel with pandas
- JSON data
- Parsing HTML with Beautiful Soup
- PyTables
MODULE 5: STATISTICS AND LINEAR ALGEBRA
- Basic statistics with NumPy
- Linear Algebra with NumPy
- Numpy random numbers
- Creating a NumPy masked array
MODULE 6: DATA VISUALIZATION
- Installation matplotlib
- Basic matplotlib plots
- Scatter plots
- Saving plots to ļ¬le
- plotting functions in pandas
MODULE 7: INTRODUCTION TO MACHINE LEARNING
- What is ML..?
- Types of ML
- Decision trees
- Linear regression
- Logistic regression
- Naive Bayes
- k-Nearest Neighbors
MODULE 8: NATURAL LANGUAGE PROCESSING
- Install nltk
- Tokenize words
- Tokenizing sentences
- Stop words with NLTK
- Stemming words with NLTK
- Speech tagging
- Sentiment analysis with NLTK
MODULE 9: INTRODUCTION TO OPENCV
- Setting up OpenCV
- Loading and displaying images
- Applying image ļ¬lters
- Tracking faces
- Face recognition
MODULE 10: WORKING WITH BIG DATA
- What is Hadoop?
- MapReduce
- File handling with Hadoopy
- Pig
- Pyspark
MACHINE LEARNING
INTRODUCTION TO MACHINE LEARNING
- What is Machine learning?
- Overview about sci-kit learn and tensorļ¬ow
- Types of ML
- Some complementing ļ¬elds of ML
- ML algorithms
- Machine learning examples
MODULE 2: REGRESSION BASED LEARNING
- Simple regression
- Multiple regression
- Logistic regression
- Predicting house prices with regression
MODULE 3: CLUSTERING BASED LEARNING
- Definition
- Types of clustering
- The k-means clustering algorithm
MODULE 4: DATA MINING
- Introducing data mining
- Decision Tree
- Affity Analysis
- Clustering
MODULE 5: CLASSIFICATION ā SENTIMENT ANALYSIS
MODULE 6: NATURAL LANGUAGE PROCESSING
- Install nltk
- Tokenize words
- Tokenizing sentences
- Stop words with NLTK
- Stemming words with NLTK
- Speech tagging
- Sentiment analysis with NLTK
MODULE 7: MAKING SENSE OF DATA THROUGH VISUALIZATION
- Introducing matplotlib
- Bar Charts
- Line Charts
- Scatter plots
- Bubble charts
MODULE 8: WORKING WITH OPENCV
- Setting up OpenCV
- Loading and displaying images
- Applying image ļ¬lters
- Tracking faces
- Face recognition
MODULE 9: PERFORMING PREDICTIONS WITH LINEAR REGRESSION
- Simple linear regression
- Multiple regression
- Training and testing model
MODULE 10: SUPPORT VECTOR MACHINES(SVM)
MODULE 11: NEURAL NETWORKS
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