Dependency disagreement between numpy, pandas, and tf-gpu

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Currently the imports as they stand break, cursory googling of the error outputs seems to be that my numpy and pandas versions are incompatible. Tensorflow also complains too. I think I want to start a new environment and build up the dependencies rather than try to resolve some sort of dependency matrix of everything here.

import requests
import pandas as pd
import sys
import os
import numpy as np
import glob
import matplotlib.pyplot as plt
import tensorflow as tf
import random
import PIL
import cv2
import seaborn as sns

from keras import regularizers, optimizers
from keras.applications.vgg16 import preprocess_input

from sklearn.preprocessing import LabelEncoder
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.metrics import classification_report, confusion_matrix
from sklearn.model_selection import train_test_split
from sklearn.utils.multiclass import unique_labels

from tensorflow.keras import activations
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Activation, BatchNormalization, Conv2D, Dense, Dropout, Flatten, MaxPooling2D, GlobalAveragePooling2D
from tensorflow.keras.layers import Input, Conv2D, ZeroPadding2D, Flatten, AveragePooling2D, Dense, Activation, Add
from tensorflow.keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.losses import CategoricalCrossentropy
from tensorflow.keras.regularizers import l2
from tensorflow.keras.callbacks import ReduceLROnPlateau, EarlyStopping

import SciServer.CasJobs as CasJobs # query with CasJobs, the primary database for the SDSS
import SciServer.SkyServer as SkyServer # show individual objects through SkyServer
import SciServer.SciDrive
import warnings