Advanced Machine Learning with Python Online Training Course Details

VLR Training provides  Advanced Machine Learning with Python online Training in Hyderabad by Industry Expert Trainers. We provide Advanced Machine Learning with Python live projects to the students and also Every day Advanced Machine Learning with Python Recorded sessions. 

Course Duration

45 Days

Mon-Fri

8 am to 10 am (IST)

Mode of Training

Online

Prerequisites for Advanced Machine Learning with Python Training

Everyone can get Advanced Machine Learning with Python training.

  • Fresher’s/Graduates
  • Job Seekers
  • Operators
  • End users
  • Developers
  • IT professionals

Advanced Machine Learning with Python

  • Python
  • Numpy
  • Pandas
  • Matplotlib
  • Seaborn
  • Timeseries
  • Machine Learning Basics
  • Basic Projects
  • Project Template
  • Internals of Machine Learning
  • Ensemble Algorithms
  • Deep Learning
  • Regular Expressions
  • NLP Basics
  • NLP Projects
  • Computer Vision Projects
  • Time Series Projects
  • Deployment
  • Operators
  • Arithmetic Operators
  • Comparison or
  • Relational Operators
  • Logical or Boolean Operators
  • Bitwise Operators
  • Assignment Operators
  • Special Operators
  • Math Library
  • Variables
  • Data Types
  • Typecasting
  • Booleans
  • Strings
  • Special Characters in a String
  • Split and Strip a String
  • Introduction to Lists
  • Lists Slicing and Reverse Order
  • Kinds of Lists
  • Concatenate Strings Using join() method
  • Add Lists
  • Introduction to Dictionary
  • Dictionary and It’s Methods
  • Nested Dictionary
  • Create Dictionary Using zip() method
  • Tuples
  • Set
  • If Condition
  • While Loop
  • Range() Method
  • For Loop
  • Reserve Keywords
  • Built-In Functions
  • User Defined Functions
  • Anonymous or Lambda Functions
  • Necessity of Numpy
  • Creation & Metadata of Numpy
  • Arrays
  • Broadcasting
  • Built-in Functions
  • Data types
  • Type casting
  • Matrix Multiplication
  • Change of Numpy
  • Shape
  • Numpy Slicing
  • Boolean Indexing
  • Filter Data
  • Statistical Methods
  • Sort, Min & Max of Numpy
    Arrays
  • Stacking & Splitting
  • Copy Vs View
  • Series
  • DataFrame
  • Metadata
  • Rename Columns & Indices
  • Transpose DataFrame
  • Slice a DataFrame
  • Boolean Indexing
  • Missing Values
  • Replace Values
  • Search, Extract & Create
    Columns
  • Set & Unset Index
  • Built-In Customised Functions
  • value_counts function
  • Groupby & Associated Methods
  • Concat & Append
  • Merge
  • Reshape – Stack & Unstack
  • Pivoting
  • Melt
  • Dummy Variables
  • Crosstab() method
  • Upper, Extract, Split & Replace Methods
  • Regular Expressions
  • Contains Method
  • StartsWith Method
  • Multiple String methods
  • Column Name Manipulation
  • Show Columns based on
    Keyword
  • read_csv() method
  • Bad Data
  • Select Columns based on
    DataType
  • Tabbed File
  • Fixed Width File
  • JSON Data
  • HTML Data
  • XML Data
  • API
  • Export Dataframe to CSV
  • Encoded Data Files
  • How to convert Non-
    Timestamp to Timestamp
  • Invalid Data
  • Unix/Epoch Time
  • Datetime Index
  • Current Datatime
  • date_range & bdate_range
    methods
  • One Axis Plot
  • Two Axis Plot
  • Line Style & Color
  • X and Y Limits
  • Line Width
  • Multiple Plots in One Chart
  • Title, X & Y Labels
  • Gridlines
  • Annotations
  • Ticks Matplotlib
  • Spines
  • Legend
  • Subplots
  • Line Plot
  • Bar Graph
  • Scatter Plot
  • Area Plot
  • Box Plot
  • Histogram
  • Pie Chart
  • Count Plot
  • Box Plot
  • Violin Plot
  • Swarm Plot
  • Overlaying Plot of Univariate Variables
  • Facet Grid
  • Lmplot & regplot
  • Size & Shape of a Plot
  • Pair Plot
  • Join Plot
  • Heat Map
  • Types of Data
  • Population Vs Sample
  • Sampling Methods
  • Branches of Statistics
  • Distribution
  • Variance Vs. Standard Deviation
  • Z-Score
  • Correlation
  • Models
  • Probability
  • Labelled Vs Unlabeled Data
  • Types of ML Algorithms
    How ML Predict things
    Count Vectorizer
  • Difference between fit and fit_transform Methods
  • Special & Numerical Chracters
  • Remove HTML Tags from Text Data
  • Remove Stop words from Text
  • Stemming
  • Train Test Split
  • Accuracy – MAE, MSE, RMSE & Variance
    Score

 

  • Simple Linear Regression
  • Multiple Linear Regression
  • Polynomial Regression
  • Classification Algorithms
  • Clustering Algorithms
  • Univariate Timeseries
    Analysis
  • Basic Algebra
  • Calculus
  • Matrices
  • Types of Variables
  • Central Tendency
  • Measures of Dispersion
  • Statistics Library
  • Sampling Techniques
  • Correlation
  • Covariance
  • Distribution
  • Central Limit Theorem
  • Confidence Interval
  • Hypothesis Testing
  • Statistical Significance
  • Loss Functions
  • Noise
  • Penalty
  • Dimensionality Reduction
  • Principal Component Analysis
  • r^2 score
  • ROC & AUROC
  • HyperParameters
  • Project Skeletons
  • Average
  • Weighted
  • Conditional
  • Bagging
  • Boosting
  • Git add
  • Git commit
  • Git push
  • Git pull
  • Git clone, etc.,
  • Data Scaling
  • Covariance
  • Eigen Values
  • Eigen Vectors
  • Artificial Neural Network
  • Deep Neural Network
  • Weight
  • Bias
  • Neuron
  • Hidden Layers
  • Input Layers
  • Output Layer
  • RNN
  • LSTM
  • CNN
  • Named Entity
  • Parts of Speech (PoS)
  • Text Cleaning
  • NGrams
  • Tokenization
  • RegEx Stemmer
  • Singular & Plural
  • Translate
  • TF-IDF
  • Anomaly Detection
  • Topic Modelling
  • Sentiment Analysis
  • Spam Classification
  • Pandas Slicing
  • Component of Datetime
  • Strftime method
  • Period Range
  • Period
  • Resample
  • Handle Timezone
  • AutoRegression
  • Moving Averages
  • ARIMA Model
  • World Bank Data
  • Google Trends Data
Accordion Content
  • Image Basics
  • Image Processing
  • Deep Learning for CV
  • Object Detection
  • Image Search Engine
  • Transfer Learning
  • SageMaker
  • Bucket Creation
  • Regression – Deep
    Learning
  • Classification – Deep
    Learning
  • Text
  • DropDown
  • Charts
  • Status
  • Checkbox, etc.,
  • HTTP Methods
  • Routing
  • Database Connectivity
  • HTTP Methods
  • Web Service Request &
    Response
  • AWS
  • Heroku
  • Google Cloud Platform
  • Azure
  • CI/CD
  • Monitoring

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