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The stochastic gradient descent optimization approach is used to train deep learning neural networks in this paper. Artificial neural networks are a subfield of deep learning that uses algorithms inspired by the structure and function of the brain. Deep learning systems are designed to learn feature hierarchies based on the composition of lower level characteristics at the top of the hierarchy. The various sorts of learning models are also discussed. We build a train and dataset with different samples (500, 2000, and 4000) and change the Epochs value in this research (100, 300 and 400).We also change the learning rate for different result. We Test the accuracy of learning rates. Classification accuracy on the training dataset is marked in blue, whereas accuracy on the test dataset is marked in orange. In This paper we find the best learning rate for good performance on the train and test sets. Keywords: Deep Learning, Epochs, Learning rate, Optimization

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This paper examined the utilization pattern of Non-Timber Forest Products (NTFPs) among the tribal population living in Bilaspur district of Chhattisgarh, India. The data for this study were generated from personal interviews of 135 respondents, who were randomly selected from nine villages of the Bilaspur district. The study showed that respondents were involved in collection of various NTFPs throughout the year. However, April-June month was found as the peak period for NTFPs collection by the respondents. All the respondents were engaged in mahua collection. Among the all collected NTFPs, the respondents had utilized mainly the fruit part of various NTFPs. The average quantities of various NTFPs collected by family-1 year-1 were as follows: 1483.25 stakes (bundles) of tendupatta, 144.51 kg of mahua and 79.25 kg of aam. The respondents consumed 70.18% of total collected quantity of kheksha followed by putu and chhatani (69.30%) and tendu (62.49%), whereas the respondents were selling 100% of total collected quantity of tendupatta and lakh followed by harra (97.94%). The data also revealed that the average annual income family-1 was maximum for mahua (` 2176.04) followed by char beej (` 1928.68) and gond (` 1888.98). The majority of respondents (94.81%) found bad weather as a main factor affecting the availability of various NTFPs. From this study, it could be concluded that collection, consumption and selling of NTFPs played a significant role in securing the livelihoods of the tribal population in the study area.