1st class free
Radhe
- Rate ₹2,323
- Response 1h
₹2,323/hr
Contact
1st class free
- English
- Classics
S you teach - Diploma, method, etc. - Your distinguishing features and everything that makes you stand out WHAT WORKS - I'm an IIT student and I teach math and physics at primary school and seco
- English
- Classics
Class location
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At Radhe 's house : Chennai
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at your home or a public place : will travel up to 20 km from Chennai
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About Radhe
#GENERAL import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt import random import math #PATH PROCESS import os import os.path from pathlib import Path import glob #IMAGE PROCESS from PIL import Image from keras.preprocessing import image from tensorflow.keras.preprocessing.image import ImageDataGenerator import cv2 from keras.applications.vgg16 import preprocess_input, decode_predictions import imageio from IPython.display import Image import matplotlib.image as mpimg #MUSIC PROCESS import pydub from scipy.io.wavfile import read, write import librosa import librosa.display import IPython from IPython.display import Audio import scipy #SCALER & TRANSFORMATION from sklearn.preprocessing import StandardScaler, OneHotEncoder from sklearn.preprocessing import MinMaxScaler from keras.utils.np_utils import to_categorical from sklearn.model_selection import train_test_split from keras import regularizers from sklearn.preprocessing import LabelEncoder #ACCURACY CONTROL from sklearn.metrics import confusion_matrix, accuracy_score, classification_report, roc_auc_score, roc_curve from sklearn.model_selection import GridSearchCV, cross_val_score from sklearn.metrics import mean_squared_error, r2_score #OPTIMIZER from keras.optimizers import RMSprop,Adam,Optimizer,Optimizer, SGD #MODEL LAYERS from tensorflow.keras.models import Sequential from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPool2D, BatchNormalization,MaxPooling2D,BatchNormalization,\ Permute, TimeDistributed, Bidirectional,GRU, SimpleRNN,\ LSTM, GlobalAveragePooling2D, SeparableConv2D, ZeroPadding2D, Convolution2D, ZeroPadding2D,Reshape,\ Conv2DTranspose, LeakyReLU, Conv1D, AveragePooling1D, MaxPooling1D from keras import models from keras import layers import tensorflow as tf from keras.applications import VGG16,VGG19,inception_v3 from keras import backend as K from keras.utils import plot_model from keras.datasets import mnist import keras #SKLEARN CLASSIFIER from xgboost import XGBClassifier, XGBRegressor from lightgbm import LGBMClassifier, LGBMRegressor from catboost import CatBoostClassifier, CatBoostRegressor from sklearn.linear_model import LogisticRegression from sklearn.naive_bayes import GaussianNB from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor from sklearn.ensemble import GradientBoostingClassifier, GradientBoostingRegressor from sklearn.ensemble import BaggingRegressor from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor from sklearn.neural_network import MLPClassifier, MLPRegressor from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor from sklearn.linear_model import LinearRegression from sklearn.cross_decomposition import PLSRegression from sklearn.linear_model import Ridge
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About the class
- All Levels
- English
- Kannada
- Urdu
- +1
All languages in which the class is available :
English
Kannada
Urdu
Punjabi
s you teach - Diploma, method, etc. - Your distinguishing features and everything that makes you stand out WHAT WORKS - I'm an IIT student and I teach math and physics at primary school and seco#GENERAL import pandas as pd import numpy as np import seaborn as sns import matplotlib.pyplot as plt import random import math #PATH PROCESS import os import os.path from pathlib import Path import glob #IMAGE PROCESS from PIL import Image from keras.preprocessing import image from tensorflow.keras.preprocessing.image import ImageDataGenerator import cv2 from keras.applications.vgg16 import preprocess_input, decode_predictions import imageio from IPython.display import Image import matplotlib.image as mpimg #MUSIC PROCESS import pydub from scipy.io.wavfile import read, write import librosa import librosa.display import IPython from IPython.display import Audio import scipy #SCALER & TRANSFORMATION from sklearn.preprocessing import StandardScaler, OneHotEncoder from sklearn.preprocessing import MinMaxScaler from keras.utils.np_utils import to_categorical from sklearn.model_selection import train_test_split from keras import regularizers from sklearn.preprocessing import LabelEncoder #ACCURACY CONTROL from sklearn.metrics import confusion_matrix, accuracy_score, classification_report, roc_auc_score, roc_curve from sklearn.model_selection import GridSearchCV, cross_val_score from sklearn.metrics import mean_squared_error, r2_score #OPTIMIZER from keras.optimizers import RMSprop,Adam,Optimizer,Optimizer, SGD #MODEL LAYERS from tensorflow.keras.models import Sequential from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPool2D, BatchNormalization,MaxPooling2D,BatchNormalization,\ Permute, TimeDistributed, Bidirectional,GRU, SimpleRNN,\ LSTM, GlobalAveragePooling2D, SeparableConv2D, ZeroPadding2D, Convolution2D, ZeroPadding2D,Reshape,\ Conv2DTranspose, LeakyReLU, Conv1D, AveragePooling1D, MaxPooling1D from keras import models from keras import layers import tensorflow as tf from keras.applications import VGG16,VGG19,inception_v3 from keras import backend as K from keras.utils import plot_model from keras.datasets import mnist import keras #SKLEARN CLASSIFIER from xgboost import XGBClassifier, XGBRegressor from lightgbm import LGBMClassifier, LGBMRegressor from catboost import CatBoostClassifier, CatBoostRegressor from sklearn.linear_model import LogisticRegression from sklearn.naive_bayes import GaussianNB from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor from sklearn.ensemble import GradientBoostingClassifier, GradientBoostingRegressor from sklearn.ensemble import BaggingRegressor from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor from sklearn.neural_network import MLPClassifier, MLPRegressor from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor from sklearn.linear_model import LinearRegression from sklearn.cross_decomposition import PLSRegression from sklearn.linear_model import Ridge
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Rates
Rate
- ₹2,323
Pack prices
- 5h: ₹10
- 10h: ₹20
free classes
This first free class with Radhe will allow you to get to know each other and to specify the exact learning requirements for the upcoming classes.
- 1hr
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